+publisher:"Texas A&M University" +contributor:("Williams, Tiffani")

Texas A&M University

1. Parthasarathy, Saranya. Bloom Filter Based Intrusion Detection for Smart Grid.

Degree: MS, Electrical Engineering, 2012, Texas A&M University

URL: http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-10768

► This thesis addresses the problem of local intrusion detection for SCADA (Supervisory Control and Data Acquisition) field devices in the smart grid. A methodology is… (more)

Subjects/Keywords: SCADA IDS; Bloom Filter Based IDS; Smart Grid IDS; IDS for SCADA System in Smart Grid

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APA (6^th Edition):

Parthasarathy, S. (2012). Bloom Filter Based Intrusion Detection for Smart Grid. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-10768

Chicago Manual of Style (16^th Edition):

Parthasarathy, Saranya. “Bloom Filter Based Intrusion Detection for Smart Grid.” 2012. Masters Thesis, Texas A&M University. Accessed April 13, 2021. http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-10768.

MLA Handbook (7^th Edition):

Parthasarathy, Saranya. “Bloom Filter Based Intrusion Detection for Smart Grid.” 2012. Web. 13 Apr 2021.

Vancouver:

Parthasarathy S. Bloom Filter Based Intrusion Detection for Smart Grid. [Internet] [Masters thesis]. Texas A&M University; 2012. [cited 2021 Apr 13]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-10768.

Council of Science Editors:

Parthasarathy S. Bloom Filter Based Intrusion Detection for Smart Grid. [Masters Thesis]. Texas A&M University; 2012. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-10768

Texas A&M University

2. Ekenna, Chinwe Pamela. Improved Sampling Based Motion Planning Through Local Learning.

Degree: PhD, Computer Science, 2016, Texas A&M University

URL: http://hdl.handle.net/1969.1/157730

► Every motion made by a moving object is either planned implicitly, e.g., human natural movement from one point to another, or explicitly, e.g., pre-planned information… (more)

▼ Every motion made by a moving object is either planned implicitly, e.g., human natural movement from one point to another, or explicitly, e.g., pre-planned information about where a robot should move in a room to effectively avoid colliding with obstacles. Motion planning is a well-studied concept in robotics and it involves moving an object from a start to goal configuration. Motion planning arises in many application domains such as robotics, computer animation (digital actors), intelligent CAD (virtual prototyping and training) and even computational biology (protein folding and drug design). Interestingly, a single class of planners, sampling-based planners have proven effective in all these domains. Probabilistic Roadmap Methods (PRMs) are one type of sampling-based planners that sample robot configurations (nodes) and connect them via viable local paths (edges) to form a roadmap containing representative feasible trajectories. The roadmap is then queried to find solution paths between start and goal configurations. Different PRM strategies perform differently given different input parameters, e.g., workspace environments and robot definitions. Motion planning, however, is computationally hard – it requires geometric path planning which has been shown to be PSPACE hard, complex representational issues for robots with known physical, geometric and temporal constraints, and challenging mapping/representing requirements for the workspace environment. Many important environments, e.g., houses, factories and airports, are heterogeneous, i.e., contain free, cluttered and narrow spaces. Heterogeneous environments, however, introduce a new set of problems for motion planning and PRM strategies because there is no ideal method suitable for all regions in the environment. In this work we introduce a technique that can adapt and apply PRM methods suitable for local regions in an environment. The basic strategy is to first identify a local region of the environment suitable for the current action based on identified neighbors. Next, based on past performance of methods in this region, adapt and pick a method to use at this time. This selection and adaptation is done by applying machine learning. By performing the local region creation in this dynamic fashion, we remove the need to explicitly partition the environment as was done in previous methods and which is difficult to do, slows down performance and includes the difficult process of determining what strategy to use even after making an explicit partitioning. Our method handles and removes these overheads. We show benefits of this approach in both planning robot motions and in protein folding simulations. We perform experiments on robots in simulation with different degrees of freedom and varying levels of heterogeneity in the environment and show an improvement in performance when our local learning method is applied. Protein folding simulations were performed on 23 proteins and we note an improvement in the quality of pathways produced with comparable performance… Advisors/Committee Members: Amato, Nancy (advisor), Scholtz, Martin J. (committee member), Williams, Tiffani (committee member), Song, Dezhen (committee member).

Subjects/Keywords: motion planning; reinforcement learning; robotics; protein folding; probabilistic roadmap methods

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Ekenna, C. P. (2016). Improved Sampling Based Motion Planning Through Local Learning. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/157730

Chicago Manual of Style (16^th Edition):

Ekenna, Chinwe Pamela. “Improved Sampling Based Motion Planning Through Local Learning.” 2016. Doctoral Dissertation, Texas A&M University. Accessed April 13, 2021. http://hdl.handle.net/1969.1/157730.

MLA Handbook (7^th Edition):

Ekenna, Chinwe Pamela. “Improved Sampling Based Motion Planning Through Local Learning.” 2016. Web. 13 Apr 2021.

Vancouver:

Ekenna CP. Improved Sampling Based Motion Planning Through Local Learning. [Internet] [Doctoral dissertation]. Texas A&M University; 2016. [cited 2021 Apr 13]. Available from: http://hdl.handle.net/1969.1/157730.

Council of Science Editors:

Ekenna CP. Improved Sampling Based Motion Planning Through Local Learning. [Doctoral Dissertation]. Texas A&M University; 2016. Available from: http://hdl.handle.net/1969.1/157730

Texas A&M University

3. Brammer, Grant. Algorithms for Searching and Analyzing Sets of Evolutionary Trees.

Degree: PhD, Computer Science and Engineering, 2014, Texas A&M University

URL: http://hdl.handle.net/1969.1/152770

► The evolutionary relationships between organisms are represented as phylogenetic trees. These trees have important implications for understanding biodiversity, tracking disease, and designing medicine. Since the… (more)

▼ The evolutionary relationships between organisms are represented as phylogenetic trees. These trees have important implications for understanding biodiversity, tracking disease, and designing medicine. Since the evolutionary process that led to modern biodiversity was not directly recorded, phylogenetic trees are inferred from modern observations. Inferring accurate phylogenies is computationally difficult and many inference algorithms produce multiple phylogenetic trees of equal quality. The common method for presenting a set of trees is to summarize their common features into a single consensus tree. Consensus methods make it easy to tell which features are common to a set of trees, but how do you explore the hypotheses that are not the majority of trees? This question is best answered by a search algorithm. We present algorithms to query a set of trees based on their internal structure. Trees can be queried based on their bipartitions, quartets, clades, subtrees, or taxa, and we present a new concept which unifies edge based relationships for search functions. To extend the power of our search functions we provide the ability to combine the results of multiple searches using set operations. We also explore the differences between sets of trees. Clustering algorithms can detect if there are multiple distinct hypotheses within a set of trees. Decision tree depth and distinguishing bipartitions can be used to measure the similarity between sets of trees. For situations where a set of trees is made up of multiple distinct sets, we present p-support which is a measure to quantify the impact of the individual sets on a single consensus tree. The algorithms are presented within the context of TreeHouse. This is my open source platform for querying and analyzing sets of trees. One goal of TreeHouse was to unite query and analysis algorithms under a single user interface. The seamless interaction between fast filtering and analysis algorithms allows users to the explore their data in a way not easily accomplished elsewhere. We believe that the algorithms in this document and in TreeHouse can shed new light on often unexplored territory. Advisors/Committee Members: Williams, Tiffani (advisor), Amato, Nancy (committee member), Welch, Jennifer (committee member), Murphy, William (committee member).

Subjects/Keywords: computer science; phylogenetics; query; algorithms

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Brammer, G. (2014). Algorithms for Searching and Analyzing Sets of Evolutionary Trees. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/152770

Chicago Manual of Style (16^th Edition):

Brammer, Grant. “Algorithms for Searching and Analyzing Sets of Evolutionary Trees.” 2014. Doctoral Dissertation, Texas A&M University. Accessed April 13, 2021. http://hdl.handle.net/1969.1/152770.

MLA Handbook (7^th Edition):

Brammer, Grant. “Algorithms for Searching and Analyzing Sets of Evolutionary Trees.” 2014. Web. 13 Apr 2021.

Vancouver:

Brammer G. Algorithms for Searching and Analyzing Sets of Evolutionary Trees. [Internet] [Doctoral dissertation]. Texas A&M University; 2014. [cited 2021 Apr 13]. Available from: http://hdl.handle.net/1969.1/152770.

Council of Science Editors:

Brammer G. Algorithms for Searching and Analyzing Sets of Evolutionary Trees. [Doctoral Dissertation]. Texas A&M University; 2014. Available from: http://hdl.handle.net/1969.1/152770

Texas A&M University

4. Cotton, Tanisha Green. Computational Study of Mean-Risk Stochastic Programs.

Degree: PhD, Industrial Engineering, 2013, Texas A&M University

URL: http://hdl.handle.net/1969.1/149619

► Mean-risk stochastic programs model uncertainty by including risk measures in the objective function. This allows for modeling risk averseness for many problems in science and… (more)

▼ Mean-risk stochastic programs model uncertainty by including risk measures in the objective function. This allows for modeling risk averseness for many problems in science and engineering. This dissertation addresses gaps in the literature on stochastic programs with mean-risk objectives. This includes a need for a computational study of the few available algorithms for this class of problems. The study was aimed at implementing and performing an empirical investigation of decomposition algorithms for stochastic linear programs with absolute semideviation (ASD) and quantile deviation (QDEV) as mean-risk measures. Specifically, the goals of the study were to analyze for specific instances how algorithms perform across different levels of risk, investigate the effect of using ASD and QDEV as risk measures, and understand when it is appropriate to use the risk-averse approach over the risk-neutral one. We derive two new subgradient based algorithms for the ASD and QDEV models, respectively. These algorithms are based on decomposing the stochastic program stage-wise and using a single (aggregated) cut in the master program to approximate the mean and deviation terms of the mean-risk objective function. We also consider a variant of each of the algorithms from the literature in which the mean-risk objective function is approximated by separate optimality cuts, one for the mean and one for the deviation term. These algorithms are implemented and applied to standard stochastic programming test instances to study their comparative performance. Both the aggregated cut and separate cut algorithms have comparable computational performance for ASD, while the separate cut algorithm outperforms its aggregate counterpart for QDEV. The computational study also reveals several insights on mean-risk stochastic linear programs. For example, the results show that for most standard test instances the risk-neutral approach is still appropriate. We show that this is the case due to the test instances having random variables with uniform marginal distributions. In contrast, when these distributions are changed to be non-uniform, the risk-averse approach is preferred. The results also show that the QDEV mean-risk measure has broader flexibility than ASD in modeling risk. Advisors/Committee Members: Ntaimo, Lewis (advisor), Butenko, Sergiy (committee member), Klutke, Georgia-Ann (committee member), Williams, Tiffani (committee member).

Subjects/Keywords: stochastic programming; mean-risk objectives; decomposition; subgradient optimization

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Cotton, T. G. (2013). Computational Study of Mean-Risk Stochastic Programs. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/149619

Chicago Manual of Style (16^th Edition):

Cotton, Tanisha Green. “Computational Study of Mean-Risk Stochastic Programs.” 2013. Doctoral Dissertation, Texas A&M University. Accessed April 13, 2021. http://hdl.handle.net/1969.1/149619.

MLA Handbook (7^th Edition):

Cotton, Tanisha Green. “Computational Study of Mean-Risk Stochastic Programs.” 2013. Web. 13 Apr 2021.

Vancouver:

Cotton TG. Computational Study of Mean-Risk Stochastic Programs. [Internet] [Doctoral dissertation]. Texas A&M University; 2013. [cited 2021 Apr 13]. Available from: http://hdl.handle.net/1969.1/149619.

Council of Science Editors:

Cotton TG. Computational Study of Mean-Risk Stochastic Programs. [Doctoral Dissertation]. Texas A&M University; 2013. Available from: http://hdl.handle.net/1969.1/149619

Texas A&M University

5. Ou, Xiaoxi 1986-. Localized Pipeline Encroachment Detector System Using Sensor Network.

Degree: MS, Electrical Engineering, 2011, Texas A&M University

URL: http://hdl.handle.net/1969.1/150952

► Detection of encroachment on pipeline right-of-way is important for pipeline safety. An effective system can provide on-time warning while reducing the probability of false alarms.… (more)

Subjects/Keywords: Wireless Sensor Network; Pipeline Safety

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APA (6^th Edition):

Ou, X. 1. (2011). Localized Pipeline Encroachment Detector System Using Sensor Network. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/150952

Chicago Manual of Style (16^th Edition):

Ou, Xiaoxi 1986-. “Localized Pipeline Encroachment Detector System Using Sensor Network.” 2011. Masters Thesis, Texas A&M University. Accessed April 13, 2021. http://hdl.handle.net/1969.1/150952.

MLA Handbook (7^th Edition):

Ou, Xiaoxi 1986-. “Localized Pipeline Encroachment Detector System Using Sensor Network.” 2011. Web. 13 Apr 2021.

Vancouver:

Ou X1. Localized Pipeline Encroachment Detector System Using Sensor Network. [Internet] [Masters thesis]. Texas A&M University; 2011. [cited 2021 Apr 13]. Available from: http://hdl.handle.net/1969.1/150952.

Council of Science Editors:

Ou X1. Localized Pipeline Encroachment Detector System Using Sensor Network. [Masters Thesis]. Texas A&M University; 2011. Available from: http://hdl.handle.net/1969.1/150952

Texas A&M University

6. Crosby, Ralph. Phylogenetic Divergence Time, Algorithms for Improved Accuracy and Performance.

Degree: PhD, Computer Science, 2015, Texas A&M University

URL: http://hdl.handle.net/1969.1/155629

► The inference of species divergence time is a key step in the study of phylogenetics. Methods have been available for the last ten years to… (more)

Subjects/Keywords: Algorithms; Phylogenetics

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APA (6^th Edition):

Crosby, R. (2015). Phylogenetic Divergence Time, Algorithms for Improved Accuracy and Performance. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/155629

Chicago Manual of Style (16^th Edition):

Crosby, Ralph. “Phylogenetic Divergence Time, Algorithms for Improved Accuracy and Performance.” 2015. Doctoral Dissertation, Texas A&M University. Accessed April 13, 2021. http://hdl.handle.net/1969.1/155629.

MLA Handbook (7^th Edition):

Crosby, Ralph. “Phylogenetic Divergence Time, Algorithms for Improved Accuracy and Performance.” 2015. Web. 13 Apr 2021.

Vancouver:

Crosby R. Phylogenetic Divergence Time, Algorithms for Improved Accuracy and Performance. [Internet] [Doctoral dissertation]. Texas A&M University; 2015. [cited 2021 Apr 13]. Available from: http://hdl.handle.net/1969.1/155629.

Council of Science Editors:

Crosby R. Phylogenetic Divergence Time, Algorithms for Improved Accuracy and Performance. [Doctoral Dissertation]. Texas A&M University; 2015. Available from: http://hdl.handle.net/1969.1/155629

Texas A&M University

7. Yeh, Hsin Yi. Uniform Sampling Framework for Sampling Based Motion Planning and Its Applications to Robotics and Protein Ligand Binding.

Degree: PhD, Computer Science, 2016, Texas A&M University

URL: http://hdl.handle.net/1969.1/157151

► Sampling-based motion planning aims to find a valid path from a start to a goal by sampling in the planning space. Planning on surfaces is… (more)

▼ Sampling-based motion planning aims to find a valid path from a start to a goal by sampling in the planning space. Planning on surfaces is an important problem in many research problems, including traditional robotics and computational biology. It is also a difficult research question to plan on surfaces as the surface is only a small subspace of the entire planning space. For example, robots are currently widely used for product assembly. Contact between the robot manipulator and the product are required to assemble each piece precisely. The configurations in which the robot fingers are in contact with the object form a surface in the planning space. However, these configurations are only a small proportion of all possible robot configurations. Several sampling-based motion planners aim to bias sampling to specific surfaces, such as Cobst surfaces, as needed for tasks requiring contact, or along the medial axis, which maximizes clearance. While some of these methods work well in practice, none of them are able to provide any information regarding the distribution of the samples they generate. It would be interesting and useful to know, for example, that a particular surface has been sampled uniformly so that one could argue regarding the probability of finding a path on that surface. Unfortunately, despite great interest for nearly two decades, it has remained an open problem to develop a method for sampling on such surfaces that can provide any information regarding the distribution of the resulting samples. Our research focuses on solving this open problem and introduces a framework that is guaranteed to uniformly sample any surface in Cspace. Instead of explicitly constructing the target surfaces, which is generally intractable, our uniform sampling framework only requires detecting intersections between a line segment and the target surface, which can often be done efficiently. Intuitively, since we uniformly distribute the line segments, the intersections between the segments and the surfaces will also be uniformly distributed. We present two particular instances of the framework: Uniform Obstacle-based PRM (UOBPRM) that uniformly samples Cobst surfaces, and Uniform Medial-Axis PRM (UMAPRM) that uniformly samples the Cspace medial axis. We provide a theoretical analysis for this framework that establishes uniformity and probabilistic completeness and also the probability of sampling in narrow passages. We show applications of this uniform sampling framework in robotics (both UOBPRM and UMAPRM) and in biology (UOBPRM). We are able to solve some difficult motion planning problems more efficiently than other sampling methods, including PRM, OBPRM, Gaussian PRM, Bridge Test PRM, and MAPRM. Moreover, we show that UOBPRM and UMAPRM have similar computational overhead as other approaches. UOBPRM is used to study the ligand binding affinity ranking problem in computational biology. Our experimental results show that UOBPRM is a potential technique to rank ligand binding affinity which can be further applied as a… Advisors/Committee Members: Amato, Nancy M. (advisor), Scholtz, J. Martin (committee member), Song, Dezhen (committee member), Williams, Tiffani L. (committee member).

Subjects/Keywords: motion planning; sampling-based motion planning; computational biology; Ligand Binding Affinity Ranking

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Yeh, H. Y. (2016). Uniform Sampling Framework for Sampling Based Motion Planning and Its Applications to Robotics and Protein Ligand Binding. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/157151

Chicago Manual of Style (16^th Edition):

Yeh, Hsin Yi. “Uniform Sampling Framework for Sampling Based Motion Planning and Its Applications to Robotics and Protein Ligand Binding.” 2016. Doctoral Dissertation, Texas A&M University. Accessed April 13, 2021. http://hdl.handle.net/1969.1/157151.

MLA Handbook (7^th Edition):

Yeh, Hsin Yi. “Uniform Sampling Framework for Sampling Based Motion Planning and Its Applications to Robotics and Protein Ligand Binding.” 2016. Web. 13 Apr 2021.

Vancouver:

Yeh HY. Uniform Sampling Framework for Sampling Based Motion Planning and Its Applications to Robotics and Protein Ligand Binding. [Internet] [Doctoral dissertation]. Texas A&M University; 2016. [cited 2021 Apr 13]. Available from: http://hdl.handle.net/1969.1/157151.

Council of Science Editors:

Yeh HY. Uniform Sampling Framework for Sampling Based Motion Planning and Its Applications to Robotics and Protein Ligand Binding. [Doctoral Dissertation]. Texas A&M University; 2016. Available from: http://hdl.handle.net/1969.1/157151

Texas A&M University

8. De Jesus Aneiro, Michael A. Statistical Analysis of Transposon Sequencing Data to Determine Essential Genes.

Degree: PhD, Computer Science, 2016, Texas A&M University

URL: http://hdl.handle.net/1969.1/159011

► Transposon Sequencing (TnSeq) has become a popular biological tool for assessing the phenotypes of large libraries of bacterial mutants at the same time. This allows… (more)

Subjects/Keywords: TnSeq; transposon mutagenesis; Bayesian Statistics; MCMC; Modeling; Classification

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APA (6^th Edition):

De Jesus Aneiro, M. A. (2016). Statistical Analysis of Transposon Sequencing Data to Determine Essential Genes. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/159011

Chicago Manual of Style (16^th Edition):

De Jesus Aneiro, Michael A. “Statistical Analysis of Transposon Sequencing Data to Determine Essential Genes.” 2016. Doctoral Dissertation, Texas A&M University. Accessed April 13, 2021. http://hdl.handle.net/1969.1/159011.

MLA Handbook (7^th Edition):

De Jesus Aneiro, Michael A. “Statistical Analysis of Transposon Sequencing Data to Determine Essential Genes.” 2016. Web. 13 Apr 2021.

Vancouver:

De Jesus Aneiro MA. Statistical Analysis of Transposon Sequencing Data to Determine Essential Genes. [Internet] [Doctoral dissertation]. Texas A&M University; 2016. [cited 2021 Apr 13]. Available from: http://hdl.handle.net/1969.1/159011.

Council of Science Editors:

De Jesus Aneiro MA. Statistical Analysis of Transposon Sequencing Data to Determine Essential Genes. [Doctoral Dissertation]. Texas A&M University; 2016. Available from: http://hdl.handle.net/1969.1/159011

Texas A&M University

9. Noor, Amina. Efficient and Robust Algorithms for Statistical Inference in Gene Regulatory Networks.

Degree: PhD, Electrical Engineering, 2013, Texas A&M University

URL: http://hdl.handle.net/1969.1/151933

► Inferring gene regulatory networks (GRNs) is of profound importance in the ﬁeld of computational biology and bioinformatics. Understanding the gene-gene and gene- transcription factor (TF)… (more)

▼ Inferring gene regulatory networks (GRNs) is of profound importance in the ﬁeld of computational biology and bioinformatics. Understanding the gene-gene and gene- transcription factor (TF) interactions has the potential of providing an insight into the complex biological processes taking place in cells. High-throughput genomic and proteomic technologies have enabled the collection of large amounts of data in order to quantify the gene expressions and mapping DNA-protein interactions. This dissertation investigates the problem of network component analysis (NCA) which estimates the transcription factor activities (TFAs) and gene-TF interactions by making use of gene expression and Chip-chip data. Closed-form solutions are provided for estimation of TF-gene connectivity matrix which yields advantage over the existing state-of-the-art methods in terms of lower computational complexity and higher consistency. We present an iterative reweighted ℓ2 norm based algorithm to infer the network connectivity when the prior knowledge about the connections is incomplete. We present an NCA algorithm which has the ability to counteract the presence of outliers in the gene expression data and is therefore more robust. Closed-form solutions are derived for the estimation of TFAs and TF-gene interactions and the resulting algorithm is comparable to the fastest algorithms proposed so far with the additional advantages of robustness to outliers and higher reliability in the TFA estimation. Finally, we look at the inference of gene regulatory networks which which essentially resumes to the estimation of only the gene-gene interactions. Gene networks are known to be sparse and therefore an inference algorithm is proposed which imposes a sparsity constraint while estimating the connectivity matrix.The online estimation lowers the computational complexity and provides superior performance in terms of accuracy and scalability. This dissertation presents gene regulatory network inference algorithms which provide computationally efficient solutions in some very crucial scenarios and give advantage over the existing algorithms and therefore provide means to give better understanding of underlying cellular network. Hence, it serves as a building block in the accurate estimation of gene regulatory networks which will pave the way for ﬁnding cures to genetic diseases. Advisors/Committee Members: Serpedin, Erchin (advisor), Nounou, Mohamed (advisor), Yoon, Byung-Jun (committee member), Karsilayan, Aydin I (committee member), Williams, Tiffani (committee member).

Subjects/Keywords: gene regulatory network; network component analysis

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APA (6^th Edition):

Noor, A. (2013). Efficient and Robust Algorithms for Statistical Inference in Gene Regulatory Networks. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/151933

Chicago Manual of Style (16^th Edition):

Noor, Amina. “Efficient and Robust Algorithms for Statistical Inference in Gene Regulatory Networks.” 2013. Doctoral Dissertation, Texas A&M University. Accessed April 13, 2021. http://hdl.handle.net/1969.1/151933.

MLA Handbook (7^th Edition):

Noor, Amina. “Efficient and Robust Algorithms for Statistical Inference in Gene Regulatory Networks.” 2013. Web. 13 Apr 2021.

Vancouver:

Noor A. Efficient and Robust Algorithms for Statistical Inference in Gene Regulatory Networks. [Internet] [Doctoral dissertation]. Texas A&M University; 2013. [cited 2021 Apr 13]. Available from: http://hdl.handle.net/1969.1/151933.

Council of Science Editors:

Noor A. Efficient and Robust Algorithms for Statistical Inference in Gene Regulatory Networks. [Doctoral Dissertation]. Texas A&M University; 2013. Available from: http://hdl.handle.net/1969.1/151933

Texas A&M University

10. Lin, Pey Chang K. Application of Logic Synthesis Toward the Inference and Control of Gene Regulatory Networks.

Degree: PhD, Electrical Engineering, 2013, Texas A&M University

URL: http://hdl.handle.net/1969.1/151088

► In the quest to understand cell behavior and cure genetic diseases such as cancer, the fundamental approach being taken is undergoing a gradual change. It… (more)

▼ In the quest to understand cell behavior and cure genetic diseases such as cancer, the fundamental approach being taken is undergoing a gradual change. It is becoming more acceptable to view these diseases as an engineering problem, and systems engineering approaches are being deployed to tackle genetic diseases. In this light, we believe that logic synthesis techniques can play a very important role. Several techniques from the field of logic synthesis can be adapted to assist in the arguably huge effort of modeling cell behavior, inferring biological networks, and controlling genetic diseases. Genes interact with other genes in a Gene Regulatory Network (GRN) and can be modeled as a Boolean Network (BN) or equivalently as a Finite State Machine (FSM). As the expression of genes deter- mine cell behavior, important problems include (i) inferring the GRN from observed gene expression data from biological measurements, and (ii) using the inferred GRN to explain how genetic diseases occur and determine the ”best” therapy towards treatment of disease. We report results on the application of logic synthesis techniques that we have developed to address both these problems. In the first technique, we present Boolean Satisfiability (SAT) based approaches to infer the predictor (logical support) of each gene that regulates melanoma, using gene expression data from patients who are suffering from the disease. From the output of such a tool, biologists can construct targeted experiments to understand the logic functions that regulate a particular target gene. Our second technique builds upon the first, in which we use a logic synthesis technique; implemented using SAT, to determine gene regulating functions for predictors and gene expression data. This technique determines a BN (or family of BNs) to describe the GRN and is validated on a synthetic network and the p53 network. The first two techniques assume binary valued gene expression data. In the third technique, we utilize continuous (analog) expression data, and present an algorithm to infer and rank predictors using modified Zhegalkin polynomials. We demonstrate our method to rank predictors for genes in the mutated mammalian and melanoma networks. The final technique assumes that the GRN is known, and uses weighted partial Max-SAT (WPMS) towards cancer therapy. In this technique, the GRN is assumed to be known. Cancer is modeled using a stuck-at fault model, and ATPG techniques are used to characterize genes leading to cancer and select drugs to treat cancer. To steer the GRN state towards a desirable healthy state, the optimal selection of drugs is formulated using WPMS. Our techniques can be used to find a set of drugs with the least side-effects, and is demonstrated in the context of growth factor pathways for colon cancer. Advisors/Committee Members: Khatri, Sunil (advisor), Dougherty, Edward (committee member), Gratz, Paul (committee member), Williams, Tiffani (committee member), Balazsi, Gabor (committee member).

Subjects/Keywords: Genomics; Logic Synthesis; Boolean Satisfiability; Gene Regulatory Networks

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Lin, P. C. K. (2013). Application of Logic Synthesis Toward the Inference and Control of Gene Regulatory Networks. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/151088

Chicago Manual of Style (16^th Edition):

Lin, Pey Chang K. “Application of Logic Synthesis Toward the Inference and Control of Gene Regulatory Networks.” 2013. Doctoral Dissertation, Texas A&M University. Accessed April 13, 2021. http://hdl.handle.net/1969.1/151088.

MLA Handbook (7^th Edition):

Lin, Pey Chang K. “Application of Logic Synthesis Toward the Inference and Control of Gene Regulatory Networks.” 2013. Web. 13 Apr 2021.

Vancouver:

Lin PCK. Application of Logic Synthesis Toward the Inference and Control of Gene Regulatory Networks. [Internet] [Doctoral dissertation]. Texas A&M University; 2013. [cited 2021 Apr 13]. Available from: http://hdl.handle.net/1969.1/151088.

Council of Science Editors:

Lin PCK. Application of Logic Synthesis Toward the Inference and Control of Gene Regulatory Networks. [Doctoral Dissertation]. Texas A&M University; 2013. Available from: http://hdl.handle.net/1969.1/151088

Texas A&M University

11. Lively, Charles. E-AMOM: An Energy-Aware Modeling and Optimization Methodology for Scientific Applications on Multicore Systems.

Degree: PhD, Computer Engineering, 2012, Texas A&M University

URL: http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-11095

► Power consumption is an important constraint in achieving efficient execution on High Performance Computing Multicore Systems. As the number of cores available on a chip… (more)

▼ Power consumption is an important constraint in achieving efficient execution on High Performance Computing Multicore Systems. As the number of cores available on a chip continues to increase, the importance of power consumption will continue to grow. In order to achieve improved performance on multicore systems scientific applications must make use of efficient methods for reducing power consumption and must further be refined to achieve reduced execution time. In this dissertation, we introduce a performance modeling framework, E-AMOM, to enable improved execution of scientific applications on parallel multicore systems with regards to a limited power budget. We develop models for each application based upon performance hardware counters. Our models utilize different performance counters for each application and for each performance component (runtime, system power consumption, CPU power consumption, and memory power consumption) that are selected via our performance-tuned principal component analysis method. Models developed through E-AMOM provide insight into the performance characteristics of each application that affect performance for each component on a parallel multicore system. Our models are more than 92% accurate across both Hybrid (MPI/OpenMP) and MPI implementations for six scientific applications. E-AMOM includes an optimization component that utilizes our models to employ run-time Dynamic Voltage and Frequency Scaling (DVFS) and Dynamic Concurrency Throttling to reduce power consumption of the scientific applications. Further, we optimize our applications based upon insights provided by the performance models to reduce runtime of the applications. Our methods and techniques are able to save up to 18% in energy consumption for Hybrid (MPI/OpenMP) and MPI scientific applications and reduce the runtime of the applications up to 11% on parallel multicore systems. Advisors/Committee Members: Taylor, Valerie E. (advisor), Kim, Eun Jung (committee member), Butler-Purry, Karen L. (committee member), Williams, Tiffani (committee member).

Subjects/Keywords: Performance Modeling; Power consumption; Multicore; Parallel Programming; MPI; Hybrid; Power prediction

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APA (6^th Edition):

Lively, C. (2012). E-AMOM: An Energy-Aware Modeling and Optimization Methodology for Scientific Applications on Multicore Systems. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-11095

Chicago Manual of Style (16^th Edition):

Lively, Charles. “E-AMOM: An Energy-Aware Modeling and Optimization Methodology for Scientific Applications on Multicore Systems.” 2012. Doctoral Dissertation, Texas A&M University. Accessed April 13, 2021. http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-11095.

MLA Handbook (7^th Edition):

Lively, Charles. “E-AMOM: An Energy-Aware Modeling and Optimization Methodology for Scientific Applications on Multicore Systems.” 2012. Web. 13 Apr 2021.

Vancouver:

Lively C. E-AMOM: An Energy-Aware Modeling and Optimization Methodology for Scientific Applications on Multicore Systems. [Internet] [Doctoral dissertation]. Texas A&M University; 2012. [cited 2021 Apr 13]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-11095.

Council of Science Editors:

Lively C. E-AMOM: An Energy-Aware Modeling and Optimization Methodology for Scientific Applications on Multicore Systems. [Doctoral Dissertation]. Texas A&M University; 2012. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-11095

Texas A&M University

12. Matthews, Suzanne. Efficient Algorithms for Comparing, Storing, and Sharing Large Collections of Phylogenetic Trees.

Degree: PhD, Computer Science, 2012, Texas A&M University

URL: http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-11124

► Evolutionary relationships between a group of organisms are commonly summarized in a phylogenetic (or evolutionary) tree. The goal of phylogenetic inference is to infer the… (more)

▼ Evolutionary relationships between a group of organisms are commonly summarized in a phylogenetic (or evolutionary) tree. The goal of phylogenetic inference is to infer the best tree structure that represents the relationships between a group of organisms, given a set of observations (e.g. molecular sequences). However, popular heuristics for inferring phylogenies output tens to hundreds of thousands of equally weighted candidate trees. Biologists summarize these trees into a single structure called the consensus tree. The central assumption is that the information discarded has less value than the information retained. But, what if this assumption is not true? In this dissertation, we demonstrate the value of retaining and studying tree collections. We also conduct an extensive literature search that highlights the rapid growth of trees produced by phylogenetic analysis. Thus, high performance algorithms are needed to accommodate this increasing production of data. We created several efficient algorithms that allow biologists to easily compare, store and share tree collections over tens to hundreds of thousands of phylogenetic trees. Universal hashing is central to all these approaches, allowing us to quickly identify the shared evolutionary relationships contained in tree collections. Our algorithms MrsRF and Phlash are the fastest in the field for comparing large collections of trees. Our algorithm TreeZip is the most efficient way to store large tree collections. Lastly, we developed Noria, a novel version control system that allows biologists to seamlessly manage and share their phylogenetic analyses. Our work has far-reaching implications for both the biological and computer science communities. We tested our algorithms on four large biological datasets, each consisting of 20; 000 to 150; 000 trees over 150 to 525 taxa. Our experimental results on these datasets indicate the long-term applicability of our algorithms to modern phylogenetic analysis, and underscore their ability to help scientists easily exchange and analyze their large tree collections. In addition to contributing to the reproducibility of phylogenetic analysis, our work enables the creation of test beds for improving phylogenetic heuristics and applications. Lastly, our data structures and algorithms can be applied to managing other tree-like data (e.g. XML). Advisors/Committee Members: Williams, Tiffani L. (advisor), Amato, Nancy M. (committee member), Welch, Jennifer L. (committee member), Woolley, James B. (committee member).

Subjects/Keywords: computer science; computational biology, bioinformatics; systematic biology; biology; evolutionary tree; phylogenetic tree; tree collections; phylogeny; compression; version control

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APA (6^th Edition):

Matthews, S. (2012). Efficient Algorithms for Comparing, Storing, and Sharing Large Collections of Phylogenetic Trees. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-11124

Chicago Manual of Style (16^th Edition):

Matthews, Suzanne. “Efficient Algorithms for Comparing, Storing, and Sharing Large Collections of Phylogenetic Trees.” 2012. Doctoral Dissertation, Texas A&M University. Accessed April 13, 2021. http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-11124.

MLA Handbook (7^th Edition):

Matthews, Suzanne. “Efficient Algorithms for Comparing, Storing, and Sharing Large Collections of Phylogenetic Trees.” 2012. Web. 13 Apr 2021.

Vancouver:

Matthews S. Efficient Algorithms for Comparing, Storing, and Sharing Large Collections of Phylogenetic Trees. [Internet] [Doctoral dissertation]. Texas A&M University; 2012. [cited 2021 Apr 13]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-11124.

Council of Science Editors:

Matthews S. Efficient Algorithms for Comparing, Storing, and Sharing Large Collections of Phylogenetic Trees. [Doctoral Dissertation]. Texas A&M University; 2012. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-11124

Texas A&M University

13. Mason, Victor Christian. Reassessing Colugo Phylogeny, Taxonomy, and Biogeography by Genome Wide Comparisons and DNA Capture Hybridization from Museum Specimens.

Degree: PhD, Genetics, 2016, Texas A&M University

URL: http://hdl.handle.net/1969.1/174236

► The ability to uncover the phylogenetic history of archived museum material with molecular techniques has rapidly improved due to the reduced cost and increased sequence… (more)

▼ The ability to uncover the phylogenetic history of archived museum material with molecular techniques has rapidly improved due to the reduced cost and increased sequence capacity of next-generation sequencing technologies. However it remains difficult to isolate large, orthologous DNA regions across multiple divergent species. Here we describe the use of cross-species DNA capture hybridization techniques and next-generation sequencing to selectively isolate and sequence mitochondrial DNA genomes and nuclear DNA from the degraded DNA of museum specimens, using probes generated from the DNA of an extant species. Colugos are among the most poorly understood of all living mammals despite their central role in our understanding of higher-level primate relationships. Two described species of these extreme gliders are the sole living members of a unique mammalian order, Dermoptera, distributed throughout Southeast Asia. We generated a draft genome sequence for a Sunda colugo and a reference alignment for the Philippine colugo, and used these to identify colugo-specific enrichment in sensory and musculoskeletal related genes that likely underlie their nocturnal and gliding adaptations. Phylogenomic analysis and catalogs of rare genomic changes overwhelmingly support the hypothesis that colugos are the sister group to primates (Primatomorpha), to the exclusion of treeshrews. We also captured ~140-kb of orthologous sequence data from colugo museum specimens sampled across their range, and identified deep genetic structure between many geographically isolated populations of the two named species, consistent with a remarkable increase in diversity. Our results identify conservation units to mitigate future losses of this enigmatic mammalian order. Examining multiple distantly related mammals we identified a consistent pattern of early diversification between east and west Borneo including colugos, the lesser mouse deer, and pangolins. This strongly parallel biogeographic pattern is not common in mammals and we see no evidence for this pattern in the greater mouse deer. Colugos on West Borneo diverged from those in Indochina in the late Pliocene, however most other mammals across this same geographic region diverged from their common ancestor much more recently in the Pleistocene. Low genetic divergence between colugos on large landmasses and colugos on neighboring islands indicate that past forest distributions in the recent past were recently much larger than present refugial distributions. Advisors/Committee Members: Murphy, William J (advisor), Helgen, Kristofer M (committee member), Samollow, Paul (committee member), Williams, Tiffani L (committee member), Cai, James (committee member).

Subjects/Keywords: colugo; sundaic biogeography; capture hybridization; mouse deer; pangolin; galeopterus; cynocephalus; tragulus; manis

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APA (6^th Edition):

Mason, V. C. (2016). Reassessing Colugo Phylogeny, Taxonomy, and Biogeography by Genome Wide Comparisons and DNA Capture Hybridization from Museum Specimens. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/174236

Chicago Manual of Style (16^th Edition):

Mason, Victor Christian. “Reassessing Colugo Phylogeny, Taxonomy, and Biogeography by Genome Wide Comparisons and DNA Capture Hybridization from Museum Specimens.” 2016. Doctoral Dissertation, Texas A&M University. Accessed April 13, 2021. http://hdl.handle.net/1969.1/174236.

MLA Handbook (7^th Edition):

Mason, Victor Christian. “Reassessing Colugo Phylogeny, Taxonomy, and Biogeography by Genome Wide Comparisons and DNA Capture Hybridization from Museum Specimens.” 2016. Web. 13 Apr 2021.

Vancouver:

Mason VC. Reassessing Colugo Phylogeny, Taxonomy, and Biogeography by Genome Wide Comparisons and DNA Capture Hybridization from Museum Specimens. [Internet] [Doctoral dissertation]. Texas A&M University; 2016. [cited 2021 Apr 13]. Available from: http://hdl.handle.net/1969.1/174236.

Council of Science Editors:

Mason VC. Reassessing Colugo Phylogeny, Taxonomy, and Biogeography by Genome Wide Comparisons and DNA Capture Hybridization from Museum Specimens. [Doctoral Dissertation]. Texas A&M University; 2016. Available from: http://hdl.handle.net/1969.1/174236

14. Manshouri, Reza. Edge Ratchet and Simulated Annealing to Improve RF Score of the Supertree of Life.

Degree: MS, Computer Science, 2017, Texas A&M University

URL: http://hdl.handle.net/1969.1/169652

► Constructing the Supertree of Life can provide crucially valuable knowledge to address many critical contemporary challenges such as fighting diseases, improving global agriculture, and protecting… (more)

Subjects/Keywords: phylogenetic; hill-climbing; simulated annealing; NP-hard

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APA (6^th Edition):

Manshouri, R. (2017). Edge Ratchet and Simulated Annealing to Improve RF Score of the Supertree of Life. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/169652

Chicago Manual of Style (16^th Edition):

Manshouri, Reza. “Edge Ratchet and Simulated Annealing to Improve RF Score of the Supertree of Life.” 2017. Masters Thesis, Texas A&M University. Accessed April 13, 2021. http://hdl.handle.net/1969.1/169652.

MLA Handbook (7^th Edition):

Manshouri, Reza. “Edge Ratchet and Simulated Annealing to Improve RF Score of the Supertree of Life.” 2017. Web. 13 Apr 2021.

Vancouver:

Manshouri R. Edge Ratchet and Simulated Annealing to Improve RF Score of the Supertree of Life. [Internet] [Masters thesis]. Texas A&M University; 2017. [cited 2021 Apr 13]. Available from: http://hdl.handle.net/1969.1/169652.

Council of Science Editors:

Manshouri R. Edge Ratchet and Simulated Annealing to Improve RF Score of the Supertree of Life. [Masters Thesis]. Texas A&M University; 2017. Available from: http://hdl.handle.net/1969.1/169652

15. Kumar, Saptaparni. Fault-Tolerant Distributed Services in Message-Passing Systems.

Degree: PhD, Computer Science, 2019, Texas A&M University

URL: http://hdl.handle.net/1969.1/186154

► Distributed systems ranging from small local area networks to large wide area networks like the Internet composed of static and/or mobile users have become increasingly… (more)

▼ Distributed systems ranging from small local area networks to large wide area networks like the Internet composed of static and/or mobile users have become increasingly popular. A desirable property for any distributed service is fault-tolerance, which means the service remains uninterrupted even if some components in the network fail. This dissertation considers weak distributed models to find either algorithms to solve certain problems or impossibility proofs to show that a problem is unsolvable. These are the main contributions of this dissertation: • Failure detectors are used as a service to solve consensus (agreement among nodes) which is otherwise impossible in failure-prone asynchronous systems. We find an algorithm for crash-failure detection that uses bounded size messages in an arbitrary, partitionable network composed of badly- behaved channels that can lose and reorder messages. • Registers are a fundamental building block for shared memory emulations on top of message passing systems. The problem has been extensively studied in static systems. However, register emulation in dynamic systems with faulty nodes is still quite hard and there are impossibility proofs that point out scenarios where change in the system composition due to nodes entering and leaving (also called churn) makes the problem unsolvable. We propose the first emulation of a crash-fault tolerant register in a system with continuous churn where consensus is unsolvable, the size of the system can grow without bound and at most a constant fraction of the number of nodes in the system can fail by crashing. We prove a lower bound that states that fault-tolerance for dynamic systems with churn is inherently lower than in static systems. • We then extend the results in the crash-fault tolerant case to a dynamic system with continuous churn and nodes that can be Byzantine faulty. It is the first emulation of an atomic register in a system that can withstand nodes continually entering and leaving, imposes no upper bound on the system size and can tolerate Byzantine nodes. However, the number of Byzantine faulty nodes that can be tolerated is upper bounded by a constant number. Although the algorithm requires that there be a constant known upper bound on the number of Byzantine nodes, this restriction is unavoidable, as we show that it is impossible to emulate an atomic register if the system size and maximum number of servers that can be Byzantine in the system is unknown. Advisors/Committee Members: Welch, Jennifer L (advisor), Jiang, Anxiao (committee member), Savari, Serap (committee member), Williams, Tiffani (committee member).

Subjects/Keywords: Distributed Computing; Fault tolerance; Lower Bounds; Algorithms

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APA (6^th Edition):

Kumar, S. (2019). Fault-Tolerant Distributed Services in Message-Passing Systems. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/186154

Chicago Manual of Style (16^th Edition):

Kumar, Saptaparni. “Fault-Tolerant Distributed Services in Message-Passing Systems.” 2019. Doctoral Dissertation, Texas A&M University. Accessed April 13, 2021. http://hdl.handle.net/1969.1/186154.

MLA Handbook (7^th Edition):

Kumar, Saptaparni. “Fault-Tolerant Distributed Services in Message-Passing Systems.” 2019. Web. 13 Apr 2021.

Vancouver:

Kumar S. Fault-Tolerant Distributed Services in Message-Passing Systems. [Internet] [Doctoral dissertation]. Texas A&M University; 2019. [cited 2021 Apr 13]. Available from: http://hdl.handle.net/1969.1/186154.

Council of Science Editors:

Kumar S. Fault-Tolerant Distributed Services in Message-Passing Systems. [Doctoral Dissertation]. Texas A&M University; 2019. Available from: http://hdl.handle.net/1969.1/186154

16. DeJesus, Michael A. Bayesian Analysis of Transposon Mutagenesis Data.

Degree: MS, Computer Science, 2012, Texas A&M University

URL: http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-11136

► Determining which genes are essential for growth of a bacterial organism is an important question to answer as it is useful for the discovery of… (more)

Subjects/Keywords: Bioinformatics; Bayesian Analysis; Gumbel; Metropolis Hastings; Sampling

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APA (6^th Edition):

DeJesus, M. A. (2012). Bayesian Analysis of Transposon Mutagenesis Data. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-11136

Chicago Manual of Style (16^th Edition):

DeJesus, Michael A. “Bayesian Analysis of Transposon Mutagenesis Data.” 2012. Masters Thesis, Texas A&M University. Accessed April 13, 2021. http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-11136.

MLA Handbook (7^th Edition):

DeJesus, Michael A. “Bayesian Analysis of Transposon Mutagenesis Data.” 2012. Web. 13 Apr 2021.

Vancouver:

DeJesus MA. Bayesian Analysis of Transposon Mutagenesis Data. [Internet] [Masters thesis]. Texas A&M University; 2012. [cited 2021 Apr 13]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-11136.

Council of Science Editors:

DeJesus MA. Bayesian Analysis of Transposon Mutagenesis Data. [Masters Thesis]. Texas A&M University; 2012. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-11136

17. Cao, Yixin. Clustering and Inconsistent Information: A Kernelization Approach.

Degree: PhD, Computer Science, 2012, Texas A&M University

URL: http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-11160

► Clustering is the unsupervised classification of patterns into groups, which is easy provided the data of patterns are consistent. However, real data are almost always… (more)

Subjects/Keywords: kernelization; clustering; feedback vertex set; fvs

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APA (6^th Edition):

Cao, Y. (2012). Clustering and Inconsistent Information: A Kernelization Approach. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-11160

Chicago Manual of Style (16^th Edition):

Cao, Yixin. “Clustering and Inconsistent Information: A Kernelization Approach.” 2012. Doctoral Dissertation, Texas A&M University. Accessed April 13, 2021. http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-11160.

MLA Handbook (7^th Edition):

Cao, Yixin. “Clustering and Inconsistent Information: A Kernelization Approach.” 2012. Web. 13 Apr 2021.

Vancouver:

Cao Y. Clustering and Inconsistent Information: A Kernelization Approach. [Internet] [Doctoral dissertation]. Texas A&M University; 2012. [cited 2021 Apr 13]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-11160.

Council of Science Editors:

Cao Y. Clustering and Inconsistent Information: A Kernelization Approach. [Doctoral Dissertation]. Texas A&M University; 2012. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-11160

18. Alamudun, Folami Tolulope. Eye Tracking Methods for Analysis of Visuo-Cognitive Behavior in Medical Imaging.

Degree: PhD, Computer Science, 2016, Texas A&M University

URL: http://hdl.handle.net/1969.1/157040

► Predictive modeling of human visual search behavior and the underlying metacognitive processes is now possible thanks to significant advances in bio-sensing device technology and machine… (more)

▼ Predictive modeling of human visual search behavior and the underlying metacognitive processes is now possible thanks to significant advances in bio-sensing device technology and machine intelligence. Eye tracking bio-sensors, for example, can measure psycho-physiological response through change events in configuration of the human eye. These events include positional changes such as visual fixation, saccadic movements, and scanpath, and non-positional changes such as blinks and pupil dilation and constriction. Using data from eye-tracking sensors, we can model human perception, cognitive processes, and responses to external stimuli. In this study, we investigated the visuo-cognitive behavior of clinicians during the diagnostic decision process for breast cancer screening under clinically equivalent experimental conditions involving multiple monitors and breast projection views. Using a head-mounted eye tracking device and a customized user interface, we recorded eye change events and diagnostic decisions from 10 clinicians (three breast-imaging radiologists and seven Radiology residents) for a corpus of 100 screening mammograms (comprising cases of varied pathology and breast parenchyma density). We proposed novel features and gaze analysis techniques, which help to encode discriminative pattern changes in positional and non-positional measures of eye events. These changes were shown to correlate with individual image readers' identity and experience level, mammographic case pathology and breast parenchyma density, and diagnostic decision. Furthermore, our results suggest that a combination of machine intelligence and bio-sensing modalities can provide adequate predictive capability for the characterization of a mammographic case and image readers diagnostic performance. Lastly, features characterizing eye movements can be utilized for biometric identification purposes. These findings are impactful in real-time performance monitoring and personalized intelligent training and evaluation systems in screening mammography. Further, the developed algorithms are applicable in other application domains involving high-risk visual tasks. Advisors/Committee Members: Hammond, Tracy A (advisor), Williams, Tiffani (committee member), Ioerger, Thomas (committee member), Ferris, Thomas (committee member).

Subjects/Keywords: Eye tracking; biometrics; mammography; diagnostic error; shapelet

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APA (6^th Edition):

Alamudun, F. T. (2016). Eye Tracking Methods for Analysis of Visuo-Cognitive Behavior in Medical Imaging. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/157040

Chicago Manual of Style (16^th Edition):

Alamudun, Folami Tolulope. “Eye Tracking Methods for Analysis of Visuo-Cognitive Behavior in Medical Imaging.” 2016. Doctoral Dissertation, Texas A&M University. Accessed April 13, 2021. http://hdl.handle.net/1969.1/157040.

MLA Handbook (7^th Edition):

Alamudun, Folami Tolulope. “Eye Tracking Methods for Analysis of Visuo-Cognitive Behavior in Medical Imaging.” 2016. Web. 13 Apr 2021.

Vancouver:

Alamudun FT. Eye Tracking Methods for Analysis of Visuo-Cognitive Behavior in Medical Imaging. [Internet] [Doctoral dissertation]. Texas A&M University; 2016. [cited 2021 Apr 13]. Available from: http://hdl.handle.net/1969.1/157040.

Council of Science Editors:

Alamudun FT. Eye Tracking Methods for Analysis of Visuo-Cognitive Behavior in Medical Imaging. [Doctoral Dissertation]. Texas A&M University; 2016. Available from: http://hdl.handle.net/1969.1/157040

19. Davis, Brian W. Resolution of Phylogenetic Relationships and Characterization of Y-Linked Microsatellites within the Big Cats, Panthera.

Degree: MS, Biomedical Science, 2010, Texas A&M University

URL: http://hdl.handle.net/1969.1/ETD-TAMU-2009-08-7048

► The pantherine lineage of cats diverged from the remainder of modern Felidae less than 11 million years ago. This clade consists of the five big… (more)

▼ The pantherine lineage of cats diverged from the remainder of modern Felidae less than 11 million years ago. This clade consists of the five big cats of the genus Panthera, the lion, tiger, jaguar, leopard, and snow leopard, as well as the closely related clouded leopard, which diverged from Panthera approximately 6 million years ago. A significant problem exists with respect to the precise phylogeny of these highly threatened great cats. Within the past four years, despite multiple publications on the subject, no two studies have reconstructed the phylogeny of Panthera with the same topology, showing particular discordance with respect to sister-taxa relationships to the lion and the position of the enigmatic snow leopard. The evolutionary relationship among these cats remains unresolved partially due to their recent and rapid radiation 3-5 million years ago, individual speciation events occurring within less than 1 million years, and probable introgression between lineages following their divergence. We assembled a 47.6 kb dataset using novel and published DNA sequence data from the autosomes, both sex chromosomes and the mitochondrial genome. This dataset was analyzed both as a supermatrix and with respect to individual partitions using maximum likelihood and Bayesian phylogeny inference. Since discord may exist among gene segments in a multilocus dataset due to their unique evolutionary histories, inference was also performed using Bayesian estimation of species trees (BEST) to form a robust consensus topology. Incongruent topologies for autosomal loci indicated phylogenetic signal conflict within the corresponding segments. We resequenced four mitochondrial and three nuclear gene segments used in recent attempts to reconstruct felid phylogeny. The newly generated data was combined with available GenBank sequence data from all published studies to highlight phylogenetic disparities stemming either from the amplification of a mitochondrial to nuclear translocation event, or errors in species identification. We provide an alternative, highly supported interpretation of the evolutionary history of the pantherine lineage using 39 single-copy regions of the felid Y chromosome and supportive phylogenetic evidence from a revised mitochondrial partition. These efforts result in a highly corroborated set of species relationships that open up new avenues for the study of speciation genomics and understanding the historical events surrounding the origin of the members of this lineage. Advisors/Committee Members: Murphy, William J. (advisor), Raudsepp, Terje (committee member), Williams, Tiffani L. (committee member).

Subjects/Keywords: Panthera; phylogenetics; Y chromosome; phylogeny; mitochondria; tiger; lion; leopard; jaguar; cats; felid; numt; BEST; Bayesian; maximum likelihood

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APA (6^th Edition):

Davis, B. W. (2010). Resolution of Phylogenetic Relationships and Characterization of Y-Linked Microsatellites within the Big Cats, Panthera. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2009-08-7048

Chicago Manual of Style (16^th Edition):

Davis, Brian W. “Resolution of Phylogenetic Relationships and Characterization of Y-Linked Microsatellites within the Big Cats, Panthera.” 2010. Masters Thesis, Texas A&M University. Accessed April 13, 2021. http://hdl.handle.net/1969.1/ETD-TAMU-2009-08-7048.

MLA Handbook (7^th Edition):

Davis, Brian W. “Resolution of Phylogenetic Relationships and Characterization of Y-Linked Microsatellites within the Big Cats, Panthera.” 2010. Web. 13 Apr 2021.

Vancouver:

Davis BW. Resolution of Phylogenetic Relationships and Characterization of Y-Linked Microsatellites within the Big Cats, Panthera. [Internet] [Masters thesis]. Texas A&M University; 2010. [cited 2021 Apr 13]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2009-08-7048.

Council of Science Editors:

Davis BW. Resolution of Phylogenetic Relationships and Characterization of Y-Linked Microsatellites within the Big Cats, Panthera. [Masters Thesis]. Texas A&M University; 2010. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2009-08-7048

20. Yi, Gang Man. Algorithms for Gene Clustering Analysis on Genomes.

Degree: PhD, Computer Science, 2012, Texas A&M University

URL: http://hdl.handle.net/1969.1/ETD-TAMU-2011-05-9384

► The increased availability of data in biological databases provides many opportunities for understanding biological processes through these data. As recent attention has shifted from sequence… (more)

▼ The increased availability of data in biological databases provides many opportunities for understanding biological processes through these data. As recent attention has shifted from sequence analysis to higher-level analysis of genes across multiple genomes, there is a need to develop efficient algorithms for these large-scale applications that can help us understand the functions of genes. The overall objective of my research was to develop improved methods which can automatically assign groups of functionally related genes in large-scale data sets by applying new gene clustering algorithms. Proposed gene clustering algorithms that can help us understand gene function and genome evolution include new algorithms for protein family classification, a window-based strategy for gene clustering on chromosomes, and an exhaustive strategy that allows all clusters of small size to be enumerated. I investigate the problems of gene clustering in multiple genomes, and define gene clustering problems using mathematical methodology and solve the problems by developing efficient and effective algorithms. For protein family classification, I developed two supervised classification algorithms that can assign proteins to existing protein families in public databases and, by taking into account similarities between the unclassified proteins, allows for progressive construction of new families from proteins that cannot be assigned. This approach is useful for rapid assignment of protein sequences from genome sequencing projects to protein families. A comparative analysis of the method to other previously developed methods shows that the algorithm has a higher accuracy rate and lower mis-classification rate when compared to algorithms that are based on the use of multiple sequence alignments and hidden Markov models. The proposed algorithm performs well even on families with very few proteins and on families with low sequence similarity. Apart from the analysis of individual sequences, identifying genomic regions that descended from a common ancestor helps us study gene function and genome evolution. In distantly related genomes, clusters of homologous gene pairs serve as evidence used in function prediction, operon detection, etc. Thus, reliable identification of gene clusters is critical to functional annotation and analysis of genes. I developed an efficient gene clustering algorithm that can be applied on hundreds of genomes at the same time. This approach allows for large-scale study of evolutionary relationships of gene clusters and study of operon formation and destruction. By placing a stricter limit on the maximum cluster size, I developed another algorithm that uses a different formulation based on constraining the overall size of a cluster and statistical estimates that allow direct comparisons of clusters of different size. A comparative analysis of proposed algorithms shows that more biological insight can be obtained by analyzing gene clusters across hundreds of genomes, which can help us understand operon occurrences,… Advisors/Committee Members: Sze, Sing-Hoi (advisor), Choe, Yoonsuck (committee member), Williams, Tiffani L. (committee member), Gill, Clare (committee member).

Subjects/Keywords: gene clustering; protein family; bioinformatics

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APA (6^th Edition):

Yi, G. M. (2012). Algorithms for Gene Clustering Analysis on Genomes. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2011-05-9384

Chicago Manual of Style (16^th Edition):

Yi, Gang Man. “Algorithms for Gene Clustering Analysis on Genomes.” 2012. Doctoral Dissertation, Texas A&M University. Accessed April 13, 2021. http://hdl.handle.net/1969.1/ETD-TAMU-2011-05-9384.

MLA Handbook (7^th Edition):

Yi, Gang Man. “Algorithms for Gene Clustering Analysis on Genomes.” 2012. Web. 13 Apr 2021.

Vancouver:

Yi GM. Algorithms for Gene Clustering Analysis on Genomes. [Internet] [Doctoral dissertation]. Texas A&M University; 2012. [cited 2021 Apr 13]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2011-05-9384.

Council of Science Editors:

Yi GM. Algorithms for Gene Clustering Analysis on Genomes. [Doctoral Dissertation]. Texas A&M University; 2012. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2011-05-9384

21. Sul, Seung Jin. Fast Hash-Based Algorithms for Analyzing Large Collections of Evolutionary Trees.

Degree: PhD, Computer Science, 2011, Texas A&M University

URL: http://hdl.handle.net/1969.1/ETD-TAMU-2009-12-7591

► Phylogenetic analysis can produce easily tens of thousands of equally plausible evolutionary trees. Consensus trees and topological distance matrices are often used to summarize the… (more)

▼ Phylogenetic analysis can produce easily tens of thousands of equally plausible evolutionary trees. Consensus trees and topological distance matrices are often used to summarize the evolutionary relationships among the trees of interest. However, current approaches are not designed to analyze very large tree collections. In this dissertation, we present two fast algorithms— HashCS and HashRF —for analyzing large collections of evolutionary trees based on a novel hash table data structure, which provides a convenient and fast approach to store and access the bipartition information collected from the tree collections. Our HashCS algorithm is a fast 𝑂(𝑛𝑡) technique for constructing consensus trees, where 𝑛 is the number of taxa and 𝑡 is the number of trees. By reprocessing the bipartition information in our hash table, HashCS constructs strict and majority consensus trees. In addition to a consensus algorithm, we design a fast topological distance algorithm called HashRF to compute the 𝑡×𝑡 Robinson-Foulds distance matrix, which requires 𝑂(𝑛𝑡^ 2) running time. A RF distance matrix provides plenty of data-mining opportunities to help researchers understand the evolutionary relationships contained in their collection of trees. We also introduce a series of extensions based on HashRF to provide researchers with more convenient set of tools for analyzing their trees. We provide extensive experimentation regarding the practical performance of our hash-based algorithms across a diverse collection of biological and artificial trees. Our results show that both algorithms easily outperform existing consensus and RF matrix implementations. For example, on our biological trees, HashCS and HashRF are 1.8 and 100 times faster than PAUP*, respectively. We show two real-world applications of our fast hashing algorithms: (i) comparing phylogenetic heuristic implementations, and (ii) clustering and visualizing trees. In our first application, we design novel methods to compare the PaupRat and Rec-I-DCM3, two popular phylogenetic heuristics that use the Maximum Parsimony criterion, and show that RF distances are more effective than parsimony scores at identifying heterogeneity within a collection of trees. In our second application, we empirically show how to determine the distinct clusters of trees within large tree collections. We use two different techniques to identify distinct tree groups. Both techniques show that partitioning the trees into distinct groups and summarizing each group separately is a better representation of the data. Additional benefits of our approach are better consensus trees as well as insightful information regarding the convergence behavior of phylogenetic heuristics. Our fast hash-based algorithms provide scientists with a very powerful tools for analyzing the relationships within their large phylogenetic tree collections in new and exciting ways. Our work has many opportunities for future work including detecting convergence and designing better heuristics. Furthermore, our hash tables have lots of… Advisors/Committee Members: Williams, Tiffani L. (advisor), Amato, Nancy M. (committee member), Gutierrez-Osuna, Ricardo (committee member), Woolley, James B. (committee member).

Subjects/Keywords: phylogenetic analysis; evolutionary tree; hash, consensus tree; Robinson-Foulds distance

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APA (6^th Edition):

Sul, S. J. (2011). Fast Hash-Based Algorithms for Analyzing Large Collections of Evolutionary Trees. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2009-12-7591

Chicago Manual of Style (16^th Edition):

Sul, Seung Jin. “Fast Hash-Based Algorithms for Analyzing Large Collections of Evolutionary Trees.” 2011. Doctoral Dissertation, Texas A&M University. Accessed April 13, 2021. http://hdl.handle.net/1969.1/ETD-TAMU-2009-12-7591.

MLA Handbook (7^th Edition):

Sul, Seung Jin. “Fast Hash-Based Algorithms for Analyzing Large Collections of Evolutionary Trees.” 2011. Web. 13 Apr 2021.

Vancouver:

Sul SJ. Fast Hash-Based Algorithms for Analyzing Large Collections of Evolutionary Trees. [Internet] [Doctoral dissertation]. Texas A&M University; 2011. [cited 2021 Apr 13]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2009-12-7591.

Council of Science Editors:

Sul SJ. Fast Hash-Based Algorithms for Analyzing Large Collections of Evolutionary Trees. [Doctoral Dissertation]. Texas A&M University; 2011. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2009-12-7591

22. Tapia, Lydia. Intelligent Motion Planning and Analysis with Probabilistic Roadmap Methods for the Study of Complex and High-Dimensional Motions.

Degree: PhD, Computer Science, 2011, Texas A&M University

URL: http://hdl.handle.net/1969.1/ETD-TAMU-2009-12-7313

► At first glance, robots and proteins have little in common. Robots are commonly thought of as tools that perform tasks such as vacuuming the floor,… (more)

▼ At first glance, robots and proteins have little in common. Robots are commonly thought of as tools that perform tasks such as vacuuming the floor, while proteins play essential roles in many biochemical processes. However, the functionality of both robots and proteins is highly dependent on their motions. In order to study motions in these two divergent domains, the same underlying algorithmic framework can be applied. This method is derived from probabilistic roadmap methods (PRMs) originally developed for robotic motion planning. It builds a graph, or roadmap, where configurations are represented as vertices and transitions between configurations are edges. The contribution of this work is a set of intelligent methods applied to PRMs. These methods facilitate both the modeling and analysis of motions, and have enabled the study of complex and high-dimensional problems in both robotic and molecular domains. In order to efficiently study biologically relevant molecular folding behaviors we have developed new techniques based on Monte Carlo solution, master equation calculation, and non-linear dimensionality reduction to run simulations and analysis on the roadmap. The first method, Map-based master equation calculation (MME), extracts global properties of the folding landscape such as global folding rates. On the other hand, another method, Map-based Monte Carlo solution (MMC), can be used to extract microscopic features of the folding process. Also, the application of dimensionality reduction returns a lower-dimensional representation that still retains the principal features while facilitating both modeling and analysis of motion landscapes. A key contribution of our methods is the flexibility to study larger and more complex structures, e.g., 372 residue Alpha-1 antitrypsin and 200 nucleotide ColE1 RNAII. We also applied intelligent roadmap-based techniques to the area of robotic motion. These methods take advantage of unsupervised learning methods at all stages of the planning process and produces solutions in complex spaces with little cost and less manual intervention compared to other adaptive methods. Our results show that our methods have low overhead and that they out-perform two existing adaptive methods in all complex cases studied. Advisors/Committee Members: Amato, Nancy M. (advisor), Choe, Yoonsuck (committee member), Scholtz, J. Martin (committee member), Welch, Jennifer (committee member), Williams, Tiffani (committee member).

Subjects/Keywords: motion planning; probabilistic roadmap methods; protein folding; RNA folding; robotics

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APA (6^th Edition):

Tapia, L. (2011). Intelligent Motion Planning and Analysis with Probabilistic Roadmap Methods for the Study of Complex and High-Dimensional Motions. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2009-12-7313

Chicago Manual of Style (16^th Edition):

Tapia, Lydia. “Intelligent Motion Planning and Analysis with Probabilistic Roadmap Methods for the Study of Complex and High-Dimensional Motions.” 2011. Doctoral Dissertation, Texas A&M University. Accessed April 13, 2021. http://hdl.handle.net/1969.1/ETD-TAMU-2009-12-7313.

MLA Handbook (7^th Edition):

Tapia, Lydia. “Intelligent Motion Planning and Analysis with Probabilistic Roadmap Methods for the Study of Complex and High-Dimensional Motions.” 2011. Web. 13 Apr 2021.

Vancouver:

Tapia L. Intelligent Motion Planning and Analysis with Probabilistic Roadmap Methods for the Study of Complex and High-Dimensional Motions. [Internet] [Doctoral dissertation]. Texas A&M University; 2011. [cited 2021 Apr 13]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2009-12-7313.

Council of Science Editors:

Tapia L. Intelligent Motion Planning and Analysis with Probabilistic Roadmap Methods for the Study of Complex and High-Dimensional Motions. [Doctoral Dissertation]. Texas A&M University; 2011. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2009-12-7313

Texas A&M University

23. Park, Hyun Jung. Large-scale analysis of phylogenetic search behavior.

Degree: MS, Computer Science, 2009, Texas A&M University

URL: http://hdl.handle.net/1969.1/ETD-TAMU-1452

► Phylogenetic analysis is used in all branches of biology by inferring evolutionary trees. Applications include designing more effective drugs, tracing the transmission of deadly viruses,… (more)

▼ Phylogenetic analysis is used in all branches of biology by inferring evolutionary trees. Applications include designing more effective drugs, tracing the transmission of deadly viruses, and guiding conservation and biodiversity efforts. Most analyses rely on effective heuristics for obtaining accurate trees. However, relatively little work has been done to analyze quantitatively the behavior of phylogenetic heuristics in tree space. This is important, because a better understanding of local search behavior can facilitate the design of better heuristics, which ultimately leads to more accurate depictions of the true evolutionary relationships. In order to access and analyze the tree search space, we implement an effec- tive local search heuristic. Having an effective heuristic that can open the space is important, since no search heuristic in this field can effectively provide data collec- tion control. So we have implemented and estimated a search heuristic, Simple Local Search or SLS, that works reasonably well in the space. Our investigations led to several interesting observations about the behavior of a search heuristic and the tree search space. We studied the correlation of tree features of search path trees, where tree features refer to the parsimony score, the Robinson- Foulds distance and the homoplasy measure. Most importantly from the results, parsimony score was highly correlated with Robinson-Foulds distance only in trees that lie on the search path to a local optimum. We also note that the scores of neighborhoods along search paths improve together, as a local search progresses. Correlations of tree features of search path trees are particularly useful in char- acterizing and controlling a search path. This paper proposes one possible stopping criterion to maximize the tree search results while minimizing computational time tested on three biological datasets using the correlation between the parsimony score and the RF distance value of search path trees. Also, the observation that scores of a neighborhood on a search path improve together gives us a significant amount of flexibility in selecting the next pivot of a search without losing performance. Eventually, our long-term goal is developing an effective search heuristic that can deal with large scale tree space in reasonable time. Improved knowledge about the tree search space and the search heuristic can provide a reasonable starting point toward the goal. Advisors/Committee Members: Williams, Tiffani L. (advisor), Sze, Sing-Hoi (committee member), Woolley, Jim (committee member).

Subjects/Keywords: phylogenetic trees; maximum parsimony

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Park, H. J. (2009). Large-scale analysis of phylogenetic search behavior. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-1452

Chicago Manual of Style (16^th Edition):

Park, Hyun Jung. “Large-scale analysis of phylogenetic search behavior.” 2009. Masters Thesis, Texas A&M University. Accessed April 13, 2021. http://hdl.handle.net/1969.1/ETD-TAMU-1452.

MLA Handbook (7^th Edition):

Park, Hyun Jung. “Large-scale analysis of phylogenetic search behavior.” 2009. Web. 13 Apr 2021.

Vancouver:

Park HJ. Large-scale analysis of phylogenetic search behavior. [Internet] [Masters thesis]. Texas A&M University; 2009. [cited 2021 Apr 13]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-1452.

Council of Science Editors:

Park HJ. Large-scale analysis of phylogenetic search behavior. [Masters Thesis]. Texas A&M University; 2009. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-1452

Texas A&M University

24. Maduike, Dumezie K. Design and Implementation of Physical Layer Network Coding Protocols.

Degree: MS, Electrical Engineering, 2010, Texas A&M University

URL: http://hdl.handle.net/1969.1/ETD-TAMU-2009-08-7194

► There has recently been growing interest in using physical layer network coding techniques to facilitate information transfer in wireless relay networks. The physical layer network… (more)

Subjects/Keywords: Signal Processing; Physical Layer; Network Coding; Analog Network Coding; Viterbi Decoding; Synchronization; Lack of Synchronization; Wireless Interference; Decode-and-Forward; Matched Filter; Timing Offset; 3-node Relay Network; SDRs; GNU Radio; USRP

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Maduike, D. K. (2010). Design and Implementation of Physical Layer Network Coding Protocols. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2009-08-7194

Chicago Manual of Style (16^th Edition):

Maduike, Dumezie K. “Design and Implementation of Physical Layer Network Coding Protocols.” 2010. Masters Thesis, Texas A&M University. Accessed April 13, 2021. http://hdl.handle.net/1969.1/ETD-TAMU-2009-08-7194.

MLA Handbook (7^th Edition):

Maduike, Dumezie K. “Design and Implementation of Physical Layer Network Coding Protocols.” 2010. Web. 13 Apr 2021.

Vancouver:

Maduike DK. Design and Implementation of Physical Layer Network Coding Protocols. [Internet] [Masters thesis]. Texas A&M University; 2010. [cited 2021 Apr 13]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2009-08-7194.

Council of Science Editors:

Maduike DK. Design and Implementation of Physical Layer Network Coding Protocols. [Masters Thesis]. Texas A&M University; 2010. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2009-08-7194

Texas A&M University

25. Lu, Yue. Improving the quality of multiple sequence alignment.

Degree: PhD, Biochemistry, 2009, Texas A&M University

URL: http://hdl.handle.net/1969.1/ETD-TAMU-3111

► Multiple sequence alignment is an important bioinformatics problem, with applications in diverse types of biological analysis, such as structure prediction, phylogenetic analysis and critical sites… (more)

▼ Multiple sequence alignment is an important bioinformatics problem, with applications in diverse types of biological analysis, such as structure prediction, phylogenetic analysis and critical sites identification. In recent years, the quality of multiple sequence alignment was improved a lot by newly developed methods, although it remains a difficult task for constructing accurate alignments, especially for divergent sequences. In this dissertation, we propose three new methods (PSAlign, ISPAlign, and NRAlign) for further improving the quality of multiple sequences alignment. In PSAlign, we propose an alternative formulation of multiple sequence alignment based on the idea of finding a multiple alignment which preserves all the pairwise alignments specified by edges of a given tree. In contrast with traditional NP-hard formulations, our preserving alignment formulation can be solved in polynomial time without using a heuristic, while still retaining very good performance when compared to traditional heuristics. In ISPAlign, by using additional hits from database search of the input sequences, a few strategies have been proposed to significantly improve alignment accuracy, including the construction of profiles from the hits while performing profile alignment, the inclusion of high scoring hits into the input sequences, the use of intermediate sequence search to link distant homologs, and the use of secondary structure information. In NRAlign, we observe that it is possible to further improve alignment accuracy by taking into account alignment of neighboring residues when aligning two residues, thus making better use of horizontal information. By modifying existing multiple alignment algorithms to make use of horizontal information, we show that this strategy is able to consistently improve over existing algorithms on all the benchmarks that are commonly used to measure alignment accuracy. Advisors/Committee Members: Sze, Sing-Hoi (advisor), Mullet, John (committee member), Scholtz, J. Martin (committee member), Williams, Tiffani (committee member).

Subjects/Keywords: Multiple Sequence Alignment; Algorithms; Bioinformatics

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Lu, Y. (2009). Improving the quality of multiple sequence alignment. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-3111

Chicago Manual of Style (16^th Edition):

Lu, Yue. “Improving the quality of multiple sequence alignment.” 2009. Doctoral Dissertation, Texas A&M University. Accessed April 13, 2021. http://hdl.handle.net/1969.1/ETD-TAMU-3111.

MLA Handbook (7^th Edition):

Lu, Yue. “Improving the quality of multiple sequence alignment.” 2009. Web. 13 Apr 2021.

Vancouver:

Lu Y. Improving the quality of multiple sequence alignment. [Internet] [Doctoral dissertation]. Texas A&M University; 2009. [cited 2021 Apr 13]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-3111.

Council of Science Editors:

Lu Y. Improving the quality of multiple sequence alignment. [Doctoral Dissertation]. Texas A&M University; 2009. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-3111

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