+publisher:"University of North Carolina" +contributor:("Wang, Wei")

University of North Carolina

1. Mahalingam, Deepika. From temporal expressions to symptom onset date identification in emergency department notes: a temporal information extraction process.

Degree: Computer Science, 2011, University of North Carolina

URL: https://cdr.lib.unc.edu/record/uuid:8b6ae6f7-411f-4ce4-9a6f-45bbcf21d395

► A patient's visit to the Emergency Department (ED) starts with the triage nurse making a note of the patient's account of the reason for the… (more)

Subjects/Keywords: College of Arts and Sciences; Department of Computer Science

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APA (6^th Edition):

Mahalingam, D. (2011). From temporal expressions to symptom onset date identification in emergency department notes: a temporal information extraction process. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:8b6ae6f7-411f-4ce4-9a6f-45bbcf21d395

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Mahalingam, Deepika. “From temporal expressions to symptom onset date identification in emergency department notes: a temporal information extraction process.” 2011. Thesis, University of North Carolina. Accessed April 13, 2021. https://cdr.lib.unc.edu/record/uuid:8b6ae6f7-411f-4ce4-9a6f-45bbcf21d395.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Mahalingam, Deepika. “From temporal expressions to symptom onset date identification in emergency department notes: a temporal information extraction process.” 2011. Web. 13 Apr 2021.

Vancouver:

Mahalingam D. From temporal expressions to symptom onset date identification in emergency department notes: a temporal information extraction process. [Internet] [Thesis]. University of North Carolina; 2011. [cited 2021 Apr 13]. Available from: https://cdr.lib.unc.edu/record/uuid:8b6ae6f7-411f-4ce4-9a6f-45bbcf21d395.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Mahalingam D. From temporal expressions to symptom onset date identification in emergency department notes: a temporal information extraction process. [Thesis]. University of North Carolina; 2011. Available from: https://cdr.lib.unc.edu/record/uuid:8b6ae6f7-411f-4ce4-9a6f-45bbcf21d395

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of North Carolina

2. Zhang, Xiang. Efficient algorithms for detecting genetic interactions in genome-wide association study.

Degree: Computer Science, 2011, University of North Carolina

URL: https://cdr.lib.unc.edu/record/uuid:7cda3a34-17e9-4073-9413-491e5c28a645

► Genome-wide association study (GWAS) aims to find genetic factors underlying complex phenotypic traits, for which epistasis or gene-gene interaction detection is often preferred over a… (more)

Subjects/Keywords: College of Arts and Sciences; Department of Computer Science

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APA (6^th Edition):

Zhang, X. (2011). Efficient algorithms for detecting genetic interactions in genome-wide association study. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:7cda3a34-17e9-4073-9413-491e5c28a645

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Zhang, Xiang. “Efficient algorithms for detecting genetic interactions in genome-wide association study.” 2011. Thesis, University of North Carolina. Accessed April 13, 2021. https://cdr.lib.unc.edu/record/uuid:7cda3a34-17e9-4073-9413-491e5c28a645.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Zhang, Xiang. “Efficient algorithms for detecting genetic interactions in genome-wide association study.” 2011. Web. 13 Apr 2021.

Vancouver:

Zhang X. Efficient algorithms for detecting genetic interactions in genome-wide association study. [Internet] [Thesis]. University of North Carolina; 2011. [cited 2021 Apr 13]. Available from: https://cdr.lib.unc.edu/record/uuid:7cda3a34-17e9-4073-9413-491e5c28a645.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Zhang X. Efficient algorithms for detecting genetic interactions in genome-wide association study. [Thesis]. University of North Carolina; 2011. Available from: https://cdr.lib.unc.edu/record/uuid:7cda3a34-17e9-4073-9413-491e5c28a645

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of North Carolina

3. Jin, Ning. Discriminative Subgraph Pattern Mining and Its Applications.

Degree: Computer Science, 2012, University of North Carolina

URL: https://cdr.lib.unc.edu/record/uuid:005a4664-fd77-435a-b458-c56daf932cd4

► My dissertation concentrates on two problems in mining discriminative subgraphs: how to efficiently identify subgraph patterns that discriminate two sets of graphs and how to… (more)

Subjects/Keywords: College of Arts and Sciences; Department of Computer Science

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APA (6^th Edition):

Jin, N. (2012). Discriminative Subgraph Pattern Mining and Its Applications. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:005a4664-fd77-435a-b458-c56daf932cd4

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Jin, Ning. “Discriminative Subgraph Pattern Mining and Its Applications.” 2012. Thesis, University of North Carolina. Accessed April 13, 2021. https://cdr.lib.unc.edu/record/uuid:005a4664-fd77-435a-b458-c56daf932cd4.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Jin, Ning. “Discriminative Subgraph Pattern Mining and Its Applications.” 2012. Web. 13 Apr 2021.

Vancouver:

Jin N. Discriminative Subgraph Pattern Mining and Its Applications. [Internet] [Thesis]. University of North Carolina; 2012. [cited 2021 Apr 13]. Available from: https://cdr.lib.unc.edu/record/uuid:005a4664-fd77-435a-b458-c56daf932cd4.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Jin N. Discriminative Subgraph Pattern Mining and Its Applications. [Thesis]. University of North Carolina; 2012. Available from: https://cdr.lib.unc.edu/record/uuid:005a4664-fd77-435a-b458-c56daf932cd4

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of North Carolina

4. Liu, Yi. Fast and Accurate Haplotype Inference with Hidden Markov Model.

Degree: Computer Science, 2013, University of North Carolina

URL: https://cdr.lib.unc.edu/record/uuid:45b26b39-77f7-4f52-b633-4b3396446583

► The genome of human and other diploid organisms consists of paired chromosomes. The haplotype information (DNA constellation on one single chromosome), which is crucial for… (more)

Subjects/Keywords: College of Arts and Sciences; Department of Computer Science

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APA (6^th Edition):

Liu, Y. (2013). Fast and Accurate Haplotype Inference with Hidden Markov Model. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:45b26b39-77f7-4f52-b633-4b3396446583

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Liu, Yi. “Fast and Accurate Haplotype Inference with Hidden Markov Model.” 2013. Thesis, University of North Carolina. Accessed April 13, 2021. https://cdr.lib.unc.edu/record/uuid:45b26b39-77f7-4f52-b633-4b3396446583.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Liu, Yi. “Fast and Accurate Haplotype Inference with Hidden Markov Model.” 2013. Web. 13 Apr 2021.

Vancouver:

Liu Y. Fast and Accurate Haplotype Inference with Hidden Markov Model. [Internet] [Thesis]. University of North Carolina; 2013. [cited 2021 Apr 13]. Available from: https://cdr.lib.unc.edu/record/uuid:45b26b39-77f7-4f52-b633-4b3396446583.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Liu Y. Fast and Accurate Haplotype Inference with Hidden Markov Model. [Thesis]. University of North Carolina; 2013. Available from: https://cdr.lib.unc.edu/record/uuid:45b26b39-77f7-4f52-b633-4b3396446583

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of North Carolina

5. Cheng, Wei. Toward Robust Group-Wise eQTL Mapping via Integrating Multi-Domain Heterogeneous Data.

Degree: Computer Science, 2015, University of North Carolina

URL: https://cdr.lib.unc.edu/record/uuid:a970ec3e-47e9-4603-b2dc-f6f2a8300847

► As a promising tool for dissecting the genetic basis of common diseases, expression quantitative trait loci (eQTL) study has attracted increasing research interest. Traditional eQTL… (more)

Subjects/Keywords: Computer science; Bioinformatics; College of Arts and Sciences; Department of Computer Science

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APA (6^th Edition):

Cheng, W. (2015). Toward Robust Group-Wise eQTL Mapping via Integrating Multi-Domain Heterogeneous Data. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:a970ec3e-47e9-4603-b2dc-f6f2a8300847

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Cheng, Wei. “Toward Robust Group-Wise eQTL Mapping via Integrating Multi-Domain Heterogeneous Data.” 2015. Thesis, University of North Carolina. Accessed April 13, 2021. https://cdr.lib.unc.edu/record/uuid:a970ec3e-47e9-4603-b2dc-f6f2a8300847.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Cheng, Wei. “Toward Robust Group-Wise eQTL Mapping via Integrating Multi-Domain Heterogeneous Data.” 2015. Web. 13 Apr 2021.

Vancouver:

Cheng W. Toward Robust Group-Wise eQTL Mapping via Integrating Multi-Domain Heterogeneous Data. [Internet] [Thesis]. University of North Carolina; 2015. [cited 2021 Apr 13]. Available from: https://cdr.lib.unc.edu/record/uuid:a970ec3e-47e9-4603-b2dc-f6f2a8300847.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Cheng W. Toward Robust Group-Wise eQTL Mapping via Integrating Multi-Domain Heterogeneous Data. [Thesis]. University of North Carolina; 2015. Available from: https://cdr.lib.unc.edu/record/uuid:a970ec3e-47e9-4603-b2dc-f6f2a8300847

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of North Carolina

6. Huang, Shunping. Correcting Reference Bias in High-throughput Sequencing Analysis.

Degree: Computer Science, 2015, University of North Carolina

URL: https://cdr.lib.unc.edu/record/uuid:44569641-9dd5-4305-845a-4b0b847f0b4a

► Mapping reads to a reference sequence is a common step when analyzing high throughput sequencing data. The choice of reference is critical because its effect… (more)

Subjects/Keywords: Computer science; Bioinformatics; College of Arts and Sciences; Department of Computer Science

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

APA (6^th Edition):

Huang, S. (2015). Correcting Reference Bias in High-throughput Sequencing Analysis. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:44569641-9dd5-4305-845a-4b0b847f0b4a

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Huang, Shunping. “Correcting Reference Bias in High-throughput Sequencing Analysis.” 2015. Thesis, University of North Carolina. Accessed April 13, 2021. https://cdr.lib.unc.edu/record/uuid:44569641-9dd5-4305-845a-4b0b847f0b4a.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Huang, Shunping. “Correcting Reference Bias in High-throughput Sequencing Analysis.” 2015. Web. 13 Apr 2021.

Vancouver:

Huang S. Correcting Reference Bias in High-throughput Sequencing Analysis. [Internet] [Thesis]. University of North Carolina; 2015. [cited 2021 Apr 13]. Available from: https://cdr.lib.unc.edu/record/uuid:44569641-9dd5-4305-845a-4b0b847f0b4a.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Huang S. Correcting Reference Bias in High-throughput Sequencing Analysis. [Thesis]. University of North Carolina; 2015. Available from: https://cdr.lib.unc.edu/record/uuid:44569641-9dd5-4305-845a-4b0b847f0b4a

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of North Carolina

7. Wang, Weibo. Detect Copy Number Variations from Read-depth of High-throughput Sequencing Data.

Degree: Computer Science, 2015, University of North Carolina

URL: https://cdr.lib.unc.edu/record/uuid:85f9311f-12ae-4a19-97c2-6f4c879a2eb3

► Copy-number variation (CNV) is a major form of genetic variation and a risk factor for various human diseases, so it is crucial to accurately detect… (more)

Subjects/Keywords: Computer science; College of Arts and Sciences; Department of Computer Science

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APA (6^th Edition):

Wang, W. (2015). Detect Copy Number Variations from Read-depth of High-throughput Sequencing Data. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:85f9311f-12ae-4a19-97c2-6f4c879a2eb3

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Wang, Weibo. “Detect Copy Number Variations from Read-depth of High-throughput Sequencing Data.” 2015. Thesis, University of North Carolina. Accessed April 13, 2021. https://cdr.lib.unc.edu/record/uuid:85f9311f-12ae-4a19-97c2-6f4c879a2eb3.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Wang, Weibo. “Detect Copy Number Variations from Read-depth of High-throughput Sequencing Data.” 2015. Web. 13 Apr 2021.

Vancouver:

Wang W. Detect Copy Number Variations from Read-depth of High-throughput Sequencing Data. [Internet] [Thesis]. University of North Carolina; 2015. [cited 2021 Apr 13]. Available from: https://cdr.lib.unc.edu/record/uuid:85f9311f-12ae-4a19-97c2-6f4c879a2eb3.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Wang W. Detect Copy Number Variations from Read-depth of High-throughput Sequencing Data. [Thesis]. University of North Carolina; 2015. Available from: https://cdr.lib.unc.edu/record/uuid:85f9311f-12ae-4a19-97c2-6f4c879a2eb3

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of North Carolina

8. Carter, Jason. Automatic Difficulty Detection.

Degree: Computer Science, 2014, University of North Carolina

URL: https://cdr.lib.unc.edu/record/uuid:a7dcfe9b-f509-4715-85a0-e167b4976c25

► Previous work has suggested that the productivity of developers increases when they help each other and as distance increases, help is offered less. One way… (more)

▼ Previous work has suggested that the productivity of developers increases when they help each other and as distance increases, help is offered less. One way to make the amount of help independent of distance is to develop a system that automatically determines and communicates developers' difficulty. It is our thesis that automatic difficulty detection is possible and useful. To provide evidence to support this thesis, we developed six novel components: * programming-activity difficulty-detection * multimodal difficulty-detection * integrated workspace-difficulty awareness * difficulty-level detection * barrier detection * reusable difficulty-detection framework Programming-activity difficulty-detection mines developers' interactions. It is based on the insight that when developers are having difficulty their edit ratio decreases while other ratios such as the debug and navigation ratios increase. This component has a low false positive rate but a high false negative rate. The high false negative rate limitation is addressed by multimodal difficulty-detection. This component mines both programmers' interactions and Kinect camera data. It is based on the insight that when developers are having difficulty, both edit ratios and postures often change. Integrated workspace-difficulty awareness combines continuous knowledge of remote users' workspace with continuous knowledge of when developers are having difficulty. Two variations of this component are possible based on whether potential helpers can replay developers' screen recordings. One limitation of this component is that sometimes, potential helpers spend a large amount of time trying to determine if they can offer help. Difficulty-level and barrier detection address this limitation. The former is based on the insight that when developers are having surmountable difficulties they tend to perform a cycle of editing and debugging their code; and when they are having insurmountable difficulties they tend to spend a large amount of time a) between actions and b) outside of the programming environment. Barrier detection infers two kinds of difficulties: incorrect output and design. This component is based the insight that when developers have incorrect output, their debug ratios increase; and when they have difficulty designing algorithms, they spend a large amount of time outside of the programming environment. The reusable difficulty-detection framework uses standard design patterns to enable programming-activity difficulty-detection to be used in two programming environments, Eclipse and Visual Studio. These components have been validated using lab and/or field studies. Advisors/Committee Members: Carter, Jason, Dewan, Prasun, Brooks, Edward F., Kelly, Diane, Stotts, P. David, Wang, Wei.

Subjects/Keywords: Computer science; College of Arts and Sciences; Department of Computer Science

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

APA (6^th Edition):

Carter, J. (2014). Automatic Difficulty Detection. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:a7dcfe9b-f509-4715-85a0-e167b4976c25

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Carter, Jason. “Automatic Difficulty Detection.” 2014. Thesis, University of North Carolina. Accessed April 13, 2021. https://cdr.lib.unc.edu/record/uuid:a7dcfe9b-f509-4715-85a0-e167b4976c25.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Carter, Jason. “Automatic Difficulty Detection.” 2014. Web. 13 Apr 2021.

Vancouver:

Carter J. Automatic Difficulty Detection. [Internet] [Thesis]. University of North Carolina; 2014. [cited 2021 Apr 13]. Available from: https://cdr.lib.unc.edu/record/uuid:a7dcfe9b-f509-4715-85a0-e167b4976c25.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Carter J. Automatic Difficulty Detection. [Thesis]. University of North Carolina; 2014. Available from: https://cdr.lib.unc.edu/record/uuid:a7dcfe9b-f509-4715-85a0-e167b4976c25

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of North Carolina

9. Zhang, Zhaojun. Efficient Computational Genetics Methods for Multiparent Crosses.

Degree: Computer Science, 2014, University of North Carolina

URL: https://cdr.lib.unc.edu/record/uuid:81496805-1c98-4416-a013-efb7fba8ee15

► Multiparent crosses are genetic populations bred in a controlled manner from a finite number of known founders. They represent experimental resources that are of potentially… (more)

Subjects/Keywords: Computer science; College of Arts and Sciences; Department of Computer Science

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

APA (6^th Edition):

Zhang, Z. (2014). Efficient Computational Genetics Methods for Multiparent Crosses. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:81496805-1c98-4416-a013-efb7fba8ee15

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Zhang, Zhaojun. “Efficient Computational Genetics Methods for Multiparent Crosses.” 2014. Thesis, University of North Carolina. Accessed April 13, 2021. https://cdr.lib.unc.edu/record/uuid:81496805-1c98-4416-a013-efb7fba8ee15.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Zhang, Zhaojun. “Efficient Computational Genetics Methods for Multiparent Crosses.” 2014. Web. 13 Apr 2021.

Vancouver:

Zhang Z. Efficient Computational Genetics Methods for Multiparent Crosses. [Internet] [Thesis]. University of North Carolina; 2014. [cited 2021 Apr 13]. Available from: https://cdr.lib.unc.edu/record/uuid:81496805-1c98-4416-a013-efb7fba8ee15.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Zhang Z. Efficient Computational Genetics Methods for Multiparent Crosses. [Thesis]. University of North Carolina; 2014. Available from: https://cdr.lib.unc.edu/record/uuid:81496805-1c98-4416-a013-efb7fba8ee15

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of North Carolina

10. Welsh, Catherine. Computational Tools to Aid the Design and Development of a Genetic Reference Population.

Degree: Computer Science, 2014, University of North Carolina

URL: https://cdr.lib.unc.edu/record/uuid:34f1001c-bc13-492c-9782-479dc0d4e987

► Model organisms are important tools used in biological and medical research. A key component of a genetics model organism is a known and reproducible genome.… (more)

▼ Model organisms are important tools used in biological and medical research. A key component of a genetics model organism is a known and reproducible genome. In the early 1900s, geneticists developed methods for fixing genomes by inbreeding. First generation genetic models used inbreeding to create disease models from animals with spontaneous or stimulated mutations. Recently, geneticists have begun to develop a second generation of models which better represent the human population in terms of diversity. One such model is the Collaborative Cross (CC), which is a mouse model derived from 8 founders. I have been involved in developing the CC since its early stages. In particular, I am interested in speeding up the inbreeding process, since it currently takes an average of thirty-six generations to achieve complete fixation. To speed up the inbreeding process, I developed a simulator that replicates the breeding process and tested various breeding strategies before applying them to a CC. To apply the simulation techniques to live mice, a fast, low-cost way to monitor their genomes at each generation was needed. As a result, two genotyping arrays were designed, a first generation array with 7,851 markers called MUGA and a second generation array called MegaMUGA with 77,800 markers. Both arrays were designed specifically to be maximally informative for the CC population. Using these genotyping arrays, one can determine from which of the eight CC founders each part of a developing mouse lines genome is inherited. I refer to these as haplotype reconstructions, and they are used as the input into my simulations as well as various other monitoring tools. To determine theaccuracy of these haplotype reconstructions, I used DNA sequencing data for three samples which were also genotyped, and compared the haplotype reconstructions from the DNA sequencing data to solutions from the genotyping array data. Advisors/Committee Members: Welsh, Catherine, McMillan, Leonard, Wang, Wei, Prins, Jan, Pardo-Manuel Pardo-Pardo-Manuel de Villena, Fernando, Valdar, William.

Subjects/Keywords: Computer science; Bioinformatics; College of Arts and Sciences; Department of Computer Science

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APA (6^th Edition):

Welsh, C. (2014). Computational Tools to Aid the Design and Development of a Genetic Reference Population. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:34f1001c-bc13-492c-9782-479dc0d4e987

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Welsh, Catherine. “Computational Tools to Aid the Design and Development of a Genetic Reference Population.” 2014. Thesis, University of North Carolina. Accessed April 13, 2021. https://cdr.lib.unc.edu/record/uuid:34f1001c-bc13-492c-9782-479dc0d4e987.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Welsh, Catherine. “Computational Tools to Aid the Design and Development of a Genetic Reference Population.” 2014. Web. 13 Apr 2021.

Vancouver:

Welsh C. Computational Tools to Aid the Design and Development of a Genetic Reference Population. [Internet] [Thesis]. University of North Carolina; 2014. [cited 2021 Apr 13]. Available from: https://cdr.lib.unc.edu/record/uuid:34f1001c-bc13-492c-9782-479dc0d4e987.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Welsh C. Computational Tools to Aid the Design and Development of a Genetic Reference Population. [Thesis]. University of North Carolina; 2014. Available from: https://cdr.lib.unc.edu/record/uuid:34f1001c-bc13-492c-9782-479dc0d4e987

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of North Carolina

11. Xie, Yuying. ROLE OF EPIDERMAL GROWTH FACTOR RECEPTOR ON CARDIAC FUNCTION.

Degree: 2015, University of North Carolina

URL: https://cdr.lib.unc.edu/record/uuid:90236d9f-a0fa-47de-b9c5-08d4a2dfe021

► The epidermal growth factor receptor (EGFR/ERBB1) was the first discovered member of the ERBB family of tyrosine kinas receptors that includes ERBB2, ERBB3 and ERBB4.… (more)

▼ The epidermal growth factor receptor (EGFR/ERBB1) was the first discovered member of the ERBB family of tyrosine kinas receptors that includes ERBB2, ERBB3 and ERBB4. After binding by EGF-related ligands, EGFR is activated to induce homodimerization or heterodimerization with other ERBB receptors, resulting in tyrosine kinase activity. Subsequently, autophosphorylation or transphosphorylation of tyrosine residues in the C-terminal tail of the receptor allows the binding of adaptor proteins to trigger intracellular signaling cascades that can lead to proliferation, survival, and anti-apoptosis. As EGFR is expressed in the majority of developing and adult tissues including heart, dysfunction of EGFR activity can cause severe damage in different tissues and even initiate cancers. Several anti-EGFR drugs are already available in the clinic for late stage cancer patients with activated EGFR activity. However, in cancer therapy using anti-ERBB2 drugs, severe cardiotoxicity among patients has been reported, emphasizing the importance of ERBB signaling in cardiac homeostasis. Also with the increases in life expectancy of patients, some types of cancers tend to be treated as a chronic disease. Therefore it is importance to understanding possible cardiac toxicity under chronic suppression of EGFR pathway. We propose the use of conditional knockout mice lacking EGFR activity in cardiomyocytes to understand the role of EGFR signaling in normal cardiac function. We demonstrated that chronic repression of EGFR pathway would cause severe cardiac dysfunction with chamber dilations, left ventricular wall thinning and depressed cardiac function. Left ventricular hypertrophy (LVH) is associated with many cardiovascular diseases and is a risk factor for cardiac related morbidity and mortality. Mice homozygous with EGFR hypomorphic mutation display various background dependent phenotypes including left ventricle hypertrophy. Using two different strains, we mapped a quantitative trait locus (QTL) associated with cardiac hypertrophy. These studies should be useful in understanding the development of LVH and in predicting patients susceptible to cardiatoxicity induced by chronic use of anti-EGFR drugs. Advisors/Committee Members: Xie, Yuying, Threadgill, David W., Manuel Pardo-Pardo-Manuel de Villena, Fernando, Wiltshire, Timothy, Sun, Wei, Wang, Wei.

Subjects/Keywords: Genetics; Molecular biology; Biology; School of Medicine; Curriculum in Genetics and Molecular Biology

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APA (6^th Edition):

Xie, Y. (2015). ROLE OF EPIDERMAL GROWTH FACTOR RECEPTOR ON CARDIAC FUNCTION. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:90236d9f-a0fa-47de-b9c5-08d4a2dfe021

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Xie, Yuying. “ROLE OF EPIDERMAL GROWTH FACTOR RECEPTOR ON CARDIAC FUNCTION.” 2015. Thesis, University of North Carolina. Accessed April 13, 2021. https://cdr.lib.unc.edu/record/uuid:90236d9f-a0fa-47de-b9c5-08d4a2dfe021.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Xie, Yuying. “ROLE OF EPIDERMAL GROWTH FACTOR RECEPTOR ON CARDIAC FUNCTION.” 2015. Web. 13 Apr 2021.

Vancouver:

Xie Y. ROLE OF EPIDERMAL GROWTH FACTOR RECEPTOR ON CARDIAC FUNCTION. [Internet] [Thesis]. University of North Carolina; 2015. [cited 2021 Apr 13]. Available from: https://cdr.lib.unc.edu/record/uuid:90236d9f-a0fa-47de-b9c5-08d4a2dfe021.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Xie Y. ROLE OF EPIDERMAL GROWTH FACTOR RECEPTOR ON CARDIAC FUNCTION. [Thesis]. University of North Carolina; 2015. Available from: https://cdr.lib.unc.edu/record/uuid:90236d9f-a0fa-47de-b9c5-08d4a2dfe021

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of North Carolina

12. Pan, Feng. Efficient algorithms in analyzing genomic data.

Degree: Computer Science, 2009, University of North Carolina

URL: https://cdr.lib.unc.edu/record/uuid:5ee3a021-169a-4cad-8c28-ab4b36444fe7

► With the development of high-throughput and low-cost genotyping technologies, immense data can be cheaply and efficiently produced for various genetic studies. A typical dataset may… (more)

▼ With the development of high-throughput and low-cost genotyping technologies, immense data can be cheaply and efficiently produced for various genetic studies. A typical dataset may contain hundreds of samples with millions of genotypes/haplotypes. In order to prevent data analysis from becoming a bottleneck, there is an evident need for fast and efficient analysis methods. My thesis focuses on two interesting and important genetic analyzing problems. Genome-wide Association mapping. The goal of genome wide association mapping is to identify genes or narrow regions in the genome which have significant statistical correlations to the given phenotypes. The discovery of these genes offers the potential for increased understanding of biological processes affecting phenotypes such as body weight and blood pressure. Sample selection for maximal Genetic Diversity. Given a large set of samples, it is usually more efficient to first conduct experiments on a small subset. Then the following question arises: What subset to use? There are many experimental scenarios where the ultimate objective is to maintain, or at least maximize, the genetic diversity within relatively small breeding populations. In my thesis, I developed the following efficient and effective algorithms to address these problems. Phylogeny-based Genom-wide association mapping: TreeQA: The algorithm uses local perfect phylogeny tree in genome wide analysis for genotype/phenotype association mapping. Samples are partitioned according to the sub-trees they belong to. The association between a tree and the phenotype is measured by some statistic tests. TreeQA+: TreeQA+ inherits all the advantages of TreeQA. Moreover, it improves TreeQA by incorporating sample correlations into the association study. Sample selection for maximal genetic diversity: Sample Selection in biallelic SNP Data: Samples are selected based on their genetic diversity among a set of SNPs. Given a set of samples, the algorithms search for the minimum subset that retains all diversity (or a high percentage of diversity). Representative Sample Selection in Non-Biallelic Data: For more general data (non-biallelic), information-theoretic measurements such as entropy and mutual information are used to measure the diversity of a sample subset. Samples are selected to maximize the original information retained. Advisors/Committee Members: Pan, Feng, Wang, Wei.

Subjects/Keywords: College of Arts and Sciences; Department of Computer Science

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

APA (6^th Edition):

Pan, F. (2009). Efficient algorithms in analyzing genomic data. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:5ee3a021-169a-4cad-8c28-ab4b36444fe7

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Pan, Feng. “Efficient algorithms in analyzing genomic data.” 2009. Thesis, University of North Carolina. Accessed April 13, 2021. https://cdr.lib.unc.edu/record/uuid:5ee3a021-169a-4cad-8c28-ab4b36444fe7.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Pan, Feng. “Efficient algorithms in analyzing genomic data.” 2009. Web. 13 Apr 2021.

Vancouver:

Pan F. Efficient algorithms in analyzing genomic data. [Internet] [Thesis]. University of North Carolina; 2009. [cited 2021 Apr 13]. Available from: https://cdr.lib.unc.edu/record/uuid:5ee3a021-169a-4cad-8c28-ab4b36444fe7.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Pan F. Efficient algorithms in analyzing genomic data. [Thesis]. University of North Carolina; 2009. Available from: https://cdr.lib.unc.edu/record/uuid:5ee3a021-169a-4cad-8c28-ab4b36444fe7

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of North Carolina

13. Liu, Jinze. New approaches for clustering high dimensional data.

Degree: Computer Science, 2006, University of North Carolina

URL: https://cdr.lib.unc.edu/record/uuid:271efd94-bcf7-42bf-8f28-bde7215cba6f

► Clustering is one of the most effective methods for analyzing datasets that contain a large number of objects with numerous attributes. Clustering seeks to identify… (more)

▼ Clustering is one of the most effective methods for analyzing datasets that contain a large number of objects with numerous attributes. Clustering seeks to identify groups, or clusters, of similar objects. In low dimensional space, the similarity between objects is often evaluated by summing the difference across all of their attributes. High dimensional data, however, may contain irrelevant attributes which mask the existence of clusters. The discovery of groups of objects that are highly similar within some subsets of relevant attributes becomes an important but challenging task. My thesis focuses on various models and algorithms for this task. We first present a flexible clustering model, namely OP-Cluster (Order Preserving Cluster). Under this model, two objects are similar on a subset of attributes if the values of these two objects induce the same relative ordering of these attributes. OPClustering algorithm has demonstrated to be useful to identify co-regulated genes in gene expression data. We also propose a semi-supervised approach to discover biologically meaningful OP-Clusters by incorporating existing gene function classifications into the clustering process. This semi-supervised algorithm yields only OP-clusters that are significantly enriched by genes from specific functional categories. Real datasets are often noisy. We propose a noise-tolerant clustering algorithm for mining frequently occuring itemsets. This algorithm is called approximate frequent itemsets (AFI). Both the theoretical and experimental results demonstrate that our AFI mining algorithm has higher recoverability of real clusters than any other existing itemset mining approaches. Pair-wise dissimilarities are often derived from original data to reduce the complexities of high dimensional data. Traditional clustering algorithms taking pair-wise dissimilarities as input often generate disjoint clusters from pair-wise dissimilarities. It is well known that the classification model represented by disjoint clusters is inconsistent with many real classifications, such gene function classifications. We develop a Poclustering algorithm, which generates overlapping clusters from pair-wise dissimilarities. We prove that by allowing overlapping clusters, Poclustering fully preserves the information of any dissimilarity matrices while traditional partitioning algorithms may cause significant information loss. Advisors/Committee Members: Liu, Jinze, Wang, Wei.

Subjects/Keywords: College of Arts and Sciences; Department of Computer Science

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

APA (6^th Edition):

Liu, J. (2006). New approaches for clustering high dimensional data. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:271efd94-bcf7-42bf-8f28-bde7215cba6f

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Liu, Jinze. “New approaches for clustering high dimensional data.” 2006. Thesis, University of North Carolina. Accessed April 13, 2021. https://cdr.lib.unc.edu/record/uuid:271efd94-bcf7-42bf-8f28-bde7215cba6f.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Liu, Jinze. “New approaches for clustering high dimensional data.” 2006. Web. 13 Apr 2021.

Vancouver:

Liu J. New approaches for clustering high dimensional data. [Internet] [Thesis]. University of North Carolina; 2006. [cited 2021 Apr 13]. Available from: https://cdr.lib.unc.edu/record/uuid:271efd94-bcf7-42bf-8f28-bde7215cba6f.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Liu J. New approaches for clustering high dimensional data. [Thesis]. University of North Carolina; 2006. Available from: https://cdr.lib.unc.edu/record/uuid:271efd94-bcf7-42bf-8f28-bde7215cba6f

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of North Carolina

14. Huan, Jun. Graph based pattern discovery in protein structures.

Degree: Computer Science, 2006, University of North Carolina

URL: https://cdr.lib.unc.edu/record/uuid:d4543b81-3017-4d83-92ff-25a818af5386

► The rapidly growing body of 3D protein structure data provides new opportunities to study the relation between protein structure and protein function. Local structure pattern… (more)

Subjects/Keywords: College of Arts and Sciences; Department of Computer Science

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

APA (6^th Edition):

Huan, J. (2006). Graph based pattern discovery in protein structures. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:d4543b81-3017-4d83-92ff-25a818af5386

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Huan, Jun. “Graph based pattern discovery in protein structures.” 2006. Thesis, University of North Carolina. Accessed April 13, 2021. https://cdr.lib.unc.edu/record/uuid:d4543b81-3017-4d83-92ff-25a818af5386.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Huan, Jun. “Graph based pattern discovery in protein structures.” 2006. Web. 13 Apr 2021.

Vancouver:

Huan J. Graph based pattern discovery in protein structures. [Internet] [Thesis]. University of North Carolina; 2006. [cited 2021 Apr 13]. Available from: https://cdr.lib.unc.edu/record/uuid:d4543b81-3017-4d83-92ff-25a818af5386.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Huan J. Graph based pattern discovery in protein structures. [Thesis]. University of North Carolina; 2006. Available from: https://cdr.lib.unc.edu/record/uuid:d4543b81-3017-4d83-92ff-25a818af5386

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of North Carolina

15. Wang, Wei. Electron transport dynamics in room temperature redox molten salts and chemistry of monolayerprotected AU nanoparticles.

Degree: Chemistry, 2006, University of North Carolina

URL: https://cdr.lib.unc.edu/record/uuid:3867518b-4a1c-45f5-8f9b-dfc4f72ee30c

► Chapter One briefly introduces the basics of redox molten salts and monolayer-protected Au nanoparticles. Chapter Two examines the mass transport of counterions in molten salts… (more)

▼ Chapter One briefly introduces the basics of redox molten salts and monolayer-protected Au nanoparticles. Chapter Two examines the mass transport of counterions in molten salts of ruthenium complexes where the counterions are mixtures of perchlorate and iodide ions. The average diffusion coefficients of the counterions were obtained by ionic conductivity impedance measurements, while that of iodide (as a surrogate for perchlorate ion transport) was measured directly using iodide voltammetry. Agreement between the conductivity-based and Faradaic counter ion transport data provides a quantitative validation of previous use of ionic conductivity data in electron transfer dynamics study in redox semi-solids. Chapter Three focuses on the ligand-exchange reaction of phenylethanethiolate (SC2Ph) ligands on 1.1 nm Au nanoparticles with varied amounts of triphenylphosphine. The results from UV-Vis, NMR and electrochemistry suggest that the reaction liberate AuISC2Ph complexes (accompanying core size change), as opposed to SC2Ph thiols, the common out-coming ligands in thiolat-to-thiolate ligand exchange reaction on Au nanoparticles. Chapter Four explores a room-temperature Au38 nanoparticle polyether melt in which voltammetric and chronoamperometric, and impedance measurements have been made, respectively, of the rates of electron and ion transport in the melt. The measured rates of electron and of electrolyte ion transport are very similar, as are their thermal activation energy barriers, observations that are consistent with a recently introduced ionic atmosphere relaxation model for control of electron transfer in redox polyethers. Chapter Five describes ferrocenated imidazolium molten phases where ferrocene is chemically linked to various dialkylimidazoliums. The physical properties, including density, fluidity, and ionic characteristics, are discussed. The electrochemical results are presented in Chapter Six. It is observed that the electron diffusion in structurally-different ferrocenated imidazoliums is more efficient than the physical transport of redox ions. The rate of electron transfer is linearly correlated to the counterion diffusion, the first observation from imidazolium-based redox semi-solids consistent with the counterion relaxation control of electron transfer model. Chapter Seven investigates the surface properties of Au nanoparticle films contacted with imidazlium ionic liquids. A dynamic contact angle change is observed and explained on the basis of anion penetration which is further compared to the formally similar electrowetting phenomenon. Advisors/Committee Members: Wang, Wei, Murray, Royce W..

Subjects/Keywords: College of Arts and Sciences; Department of Chemistry

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

APA (6^th Edition):

Wang, W. (2006). Electron transport dynamics in room temperature redox molten salts and chemistry of monolayerprotected AU nanoparticles. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:3867518b-4a1c-45f5-8f9b-dfc4f72ee30c

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Wang, Wei. “Electron transport dynamics in room temperature redox molten salts and chemistry of monolayerprotected AU nanoparticles.” 2006. Thesis, University of North Carolina. Accessed April 13, 2021. https://cdr.lib.unc.edu/record/uuid:3867518b-4a1c-45f5-8f9b-dfc4f72ee30c.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Wang, Wei. “Electron transport dynamics in room temperature redox molten salts and chemistry of monolayerprotected AU nanoparticles.” 2006. Web. 13 Apr 2021.

Vancouver:

Wang W. Electron transport dynamics in room temperature redox molten salts and chemistry of monolayerprotected AU nanoparticles. [Internet] [Thesis]. University of North Carolina; 2006. [cited 2021 Apr 13]. Available from: https://cdr.lib.unc.edu/record/uuid:3867518b-4a1c-45f5-8f9b-dfc4f72ee30c.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Wang W. Electron transport dynamics in room temperature redox molten salts and chemistry of monolayerprotected AU nanoparticles. [Thesis]. University of North Carolina; 2006. Available from: https://cdr.lib.unc.edu/record/uuid:3867518b-4a1c-45f5-8f9b-dfc4f72ee30c

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of North Carolina

16. Zhang, Qi. Mining emerging massive scientific sequence data using block-wise decomposition methods.

Degree: Computer Science, 2009, University of North Carolina

URL: https://cdr.lib.unc.edu/record/uuid:c5c13eda-230e-4cae-826e-e21af96ae55a

► I present efficient data mining algorithms for knowledge discovery on two types of emerging large-scale sequence-based scientific datasets: 1) static sequence data generated from SNP… (more)

▼ I present efficient data mining algorithms for knowledge discovery on two types of emerging large-scale sequence-based scientific datasets: 1) static sequence data generated from SNP diversity arrays for genomic studies, and 2) dynamic sequence data collected in streaming and sensor network systems for environmental studies. The massive, noisy nature of the SNP arrays and the distributive, online nature of sensor network data pose challenging issues for knowledge discovery such as scalability, robustness, and efficiency. Despite the different characteristics of the SNP arrays and streaming sensor data, when viewed as sequences of ordered observations, both can be efficiently mined using algorithms based on block-wise decomposition methods. I present models and mining algorithms for inferring the genetic variation structure in genome-wide Single-Nucleotide Polymorphism (SNP) arrays. Genome-wide SNP arrays provide a comprehensive view of genome variation and serve as powerful resources for genetic and biomedical studies. Understanding the patterns of genetic variation in a population of individuals plays an important role in solving many genetics problems such as genealogy reconstruction and gene association studies. In this thesis, I propose data mining models and algorithms to efficiently infer genetic variation structure from the massive SNP panels of recombinant sequences resulting from meiotic recombination. I introduced the Minimum Segmentation Problem (MSP) to infer the segmentation structure of a single recombinant strain, as well as the Minimum Mosaic Problem (MMP) to infer the mosaic structure on a panel of recombinant strains. Both MSP and MMP estimate the ancestral polymorphism patterns exhibited in recombinant strains which provides important inputs for the subsequent association analysis. Efficient dynamic programming and graph algorithms based on block-wise decomposition are proposed which can solve MSP and MMP on genome-wide large-scale panels. I present efficient algorithms for mining massive streaming and sensor network data for observational sciences such as ecology and environmental studies. I proposed efficient algorithms using block-wise synopsis construction to capture the data distribution online for the dynamic sequence data collected in the sensor network and streaming systems including clustering analysis and order-statistics computation, which is critical for real-time monitoring, anomaly detection, and other domain specific analysis. Advisors/Committee Members: Zhang, Qi, Wang, Wei, University of North Carolina at Chapel Hill.

Subjects/Keywords: College of Arts and Sciences; Department of Computer Science

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

APA (6^th Edition):

Zhang, Q. (2009). Mining emerging massive scientific sequence data using block-wise decomposition methods. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:c5c13eda-230e-4cae-826e-e21af96ae55a

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Zhang, Qi. “Mining emerging massive scientific sequence data using block-wise decomposition methods.” 2009. Thesis, University of North Carolina. Accessed April 13, 2021. https://cdr.lib.unc.edu/record/uuid:c5c13eda-230e-4cae-826e-e21af96ae55a.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Zhang, Qi. “Mining emerging massive scientific sequence data using block-wise decomposition methods.” 2009. Web. 13 Apr 2021.

Vancouver:

Zhang Q. Mining emerging massive scientific sequence data using block-wise decomposition methods. [Internet] [Thesis]. University of North Carolina; 2009. [cited 2021 Apr 13]. Available from: https://cdr.lib.unc.edu/record/uuid:c5c13eda-230e-4cae-826e-e21af96ae55a.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Zhang Q. Mining emerging massive scientific sequence data using block-wise decomposition methods. [Thesis]. University of North Carolina; 2009. Available from: https://cdr.lib.unc.edu/record/uuid:c5c13eda-230e-4cae-826e-e21af96ae55a

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

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Open Access Theses and Dissertations