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You searched for +publisher:"Georgia Tech" +contributor:("Jones, Dean P."). Showing records 1 – 2 of 2 total matches.

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Georgia Tech

1. Uppal, Karan. Translational bioinformatics for personalized medicine and integrative biology: Data integration, extraction, knowledge discovery, and visualization.

Degree: PhD, Biology, 2015, Georgia Tech

This thesis focuses on developing a computational framework to support the Precision Medicine Initiative. The newly developed tools and algorithms use machine learning, text mining and visualization techniques for extracting salient information from heterogeneous sources such as scientific literature, clinical text, and –omics technologies to enhance clinical decision making and improve the quality of healthcare. Various advances in biomedical technologies have enhanced our ability to study disease processes at different molecular levels (genes, metabolites, histones, etc.). Similarly, technological advances in healthcare domain such as adoption of Electronic Health Record systems (EHRs) provide us a unique opportunity to develop a learning healthcare system where intelligent tools and algorithms can be utilized to extract information from clinical notes, patient medication records, laboratory results, etc. for early detection of medical risks and prevention of adverse drug events. The key novel contributions of this thesis are: a) development of novel full-text summarization algorithms that have been incorporated into a web application (CoReViz) for visualizing clinically relevant information and extracting relevant sentences from clinical text and scientific articles; b) development of novel association mining algorithms and graph summarization techniques incorporated into a web application (SEACOIN2.0) for interactive drill-down summarization and hypothesis generation to extend the functionality of PubMed; c) introduction of the concept of literature based Phenotype-wide Association Studies (Lit-PheWAS); d) development of an ensemble feature selection framework for biomarker discovery using agent-based modeling and stochastic optimization techniques. Advisors/Committee Members: Lee, Eva K. (advisor), Navathe, Shamkant B. (committee member), Jordan, King (committee member), Fan, Yuhong (committee member), Jones, Dean P. (committee member).

Subjects/Keywords: Literature mining; Literature-based discovery; Text mining; Text summarization; Visualization; Content recognition; Feature selection; Data mining

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

APA (6th Edition):

Uppal, K. (2015). Translational bioinformatics for personalized medicine and integrative biology: Data integration, extraction, knowledge discovery, and visualization. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/55548

Chicago Manual of Style (16th Edition):

Uppal, Karan. “Translational bioinformatics for personalized medicine and integrative biology: Data integration, extraction, knowledge discovery, and visualization.” 2015. Doctoral Dissertation, Georgia Tech. Accessed August 03, 2020. http://hdl.handle.net/1853/55548.

MLA Handbook (7th Edition):

Uppal, Karan. “Translational bioinformatics for personalized medicine and integrative biology: Data integration, extraction, knowledge discovery, and visualization.” 2015. Web. 03 Aug 2020.

Vancouver:

Uppal K. Translational bioinformatics for personalized medicine and integrative biology: Data integration, extraction, knowledge discovery, and visualization. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2020 Aug 03]. Available from: http://hdl.handle.net/1853/55548.

Council of Science Editors:

Uppal K. Translational bioinformatics for personalized medicine and integrative biology: Data integration, extraction, knowledge discovery, and visualization. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/55548


Georgia Tech

2. Kniss-James, Ariel Seitz. Analysis of calcium and hydrogen peroxide frequency responses in T cells at single-cell resolution via microfluidic traps.

Degree: PhD, Biomedical Engineering (Joint GT/Emory Department), 2016, Georgia Tech

As a key component of the adaptive immune response, T cell lymphocytes are widely studied but often difficult to isolate and visualize for experimentation with single-cell resolution. Intracellular signaling upon activation of the T cell receptor is necessary for proper immune function. The resulting cytosolic calcium concentration has been shown to oscillate, differentially encoding downstream transcription factors. Additionally, activation also requires the concurrent signaling of hydrogen peroxide, with implications on protein and channel functions between these signaling networks. However, the direct mechanisms and connections are difficult to analyze due to the fast, dynamic signaling and subcellular localization. Frequency response analysis, originally developed in control engineering for discerning complex, interconnected networks that are difficult to interrogate with bulk measurements, has been shown to be useful for analyzing biological systems and helps with identifying dominant interactions within the network. We utilize this technique to probe intracellular calcium dynamics in the frequency domain to better investigate the relationship between hydrogen peroxide and calcium. To enable single-cell studies of intracellular T cell signaling dynamics using frequency response analysis, we developed complementary computational and microfluidic tools necessary for single-cell trapping, stimulation, imaging, and analysis. This novel platform provides a systematic approach for analyzing T cell signaling in the frequency domain and is applicable for assessing many biological questions. Stimulation with oscillatory hydrogen peroxide solutions identified specific input frequencies that facilitate entrainment of calcium signaling and we observe heterogeneous responses within the population, illustrating the necessity of single-cell analysis to understand the realm of potential responses. Jurkat T cells were found to respond robustly to input oscillations of 2.78 mHz frequency, corresponding to a period of 6 minutes. We extended this analysis by switching the input and output signals such that cells were exposed to oscillatory calcium solutions and localized intracellular hydrogen peroxide was measured using two variants of the reporter protein, HyPer. Calcium stimulated hydrogen peroxide dynamics vary depending on location of the reporter within the cell and this difference in signaling dynamics suggests altered regulatory mechanisms for calcium-hydrogen peroxide crosstalk dependent on subcellular localization. We also report the first investigation of the downstream transcriptional response using smFISH analysis following oscillatory stimulation with cytoplasmic calcium signaling. These findings uphold our previous natural frequency result of approximately 2.78 mHz as our smFISH response was maximal at this frequency, connecting the functional consequence with upstream frequency-based signaling. In summary, this thesis developed experimental and computational techniques to robustly deliver oscillatory stimulation to… Advisors/Committee Members: Kemp, Melissa L. (advisor), Lu, Hang (advisor), Voit, Eberhard O. (committee member), Egerstedt, Magnus (committee member), Jones, Dean P. (committee member), Zhu, Cheng (committee member).

Subjects/Keywords: T cell; Frequency response analysis; Hydrogen peroxide signaling; Calcium oscillations; Single-cell analysis

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

APA (6th Edition):

Kniss-James, A. S. (2016). Analysis of calcium and hydrogen peroxide frequency responses in T cells at single-cell resolution via microfluidic traps. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/58586

Chicago Manual of Style (16th Edition):

Kniss-James, Ariel Seitz. “Analysis of calcium and hydrogen peroxide frequency responses in T cells at single-cell resolution via microfluidic traps.” 2016. Doctoral Dissertation, Georgia Tech. Accessed August 03, 2020. http://hdl.handle.net/1853/58586.

MLA Handbook (7th Edition):

Kniss-James, Ariel Seitz. “Analysis of calcium and hydrogen peroxide frequency responses in T cells at single-cell resolution via microfluidic traps.” 2016. Web. 03 Aug 2020.

Vancouver:

Kniss-James AS. Analysis of calcium and hydrogen peroxide frequency responses in T cells at single-cell resolution via microfluidic traps. [Internet] [Doctoral dissertation]. Georgia Tech; 2016. [cited 2020 Aug 03]. Available from: http://hdl.handle.net/1853/58586.

Council of Science Editors:

Kniss-James AS. Analysis of calcium and hydrogen peroxide frequency responses in T cells at single-cell resolution via microfluidic traps. [Doctoral Dissertation]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/58586

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