Discrete Algorithms for Analysis of Genotype Data
Accessibility of high-throughput genotyping technology makes possible genome-wide association studies for common complex diseases. When dealing with common diseases, it is necessary to search and analyze multiple independent causes resulted from interactions of multiple genes scattered over the enti...
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ndltd-GEORGIA-oai-digitalarchive.gsu.edu-cs_diss-10182013-04-23T03:18:55Z Discrete Algorithms for Analysis of Genotype Data Brinza, Dumitru Accessibility of high-throughput genotyping technology makes possible genome-wide association studies for common complex diseases. When dealing with common diseases, it is necessary to search and analyze multiple independent causes resulted from interactions of multiple genes scattered over the entire genome. The optimization formulations for searching disease-associated risk/resistant factors and predicting disease susceptibility for given case-control study have been introduced. Several discrete methods for disease association search exploiting greedy strategy and topological properties of case-control studies have been developed. New disease susceptibility prediction methods based on the developed search methods have been validated on datasets from case-control studies for several common diseases. Our experiments compare favorably the proposed algorithms with the existing association search and susceptibility prediction methods. 2007-06-29 text application/pdf http://digitalarchive.gsu.edu/cs_diss/19 http://digitalarchive.gsu.edu/cgi/viewcontent.cgi?article=1018&context=cs_diss Computer Science Dissertations Digital Archive @ GSU haplotype combinatorialmethods optimization risk factor disease association case-control study phasing genotype SNP algorithm Computer Sciences |
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haplotype combinatorialmethods optimization risk factor disease association case-control study phasing genotype SNP algorithm Computer Sciences |
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haplotype combinatorialmethods optimization risk factor disease association case-control study phasing genotype SNP algorithm Computer Sciences Brinza, Dumitru Discrete Algorithms for Analysis of Genotype Data |
description |
Accessibility of high-throughput genotyping technology makes possible genome-wide association studies for common complex diseases. When dealing with common diseases, it is necessary to search and analyze multiple independent causes resulted from interactions of multiple genes scattered over the entire genome. The optimization formulations for searching disease-associated risk/resistant factors and predicting disease susceptibility for given case-control study have been introduced. Several discrete methods for disease association search exploiting greedy strategy and topological properties of case-control studies have been developed. New disease susceptibility prediction methods based on the developed search methods have been validated on datasets from case-control studies for several common diseases. Our experiments compare favorably the proposed algorithms with the existing association search and susceptibility prediction methods. |
author |
Brinza, Dumitru |
author_facet |
Brinza, Dumitru |
author_sort |
Brinza, Dumitru |
title |
Discrete Algorithms for Analysis of Genotype Data |
title_short |
Discrete Algorithms for Analysis of Genotype Data |
title_full |
Discrete Algorithms for Analysis of Genotype Data |
title_fullStr |
Discrete Algorithms for Analysis of Genotype Data |
title_full_unstemmed |
Discrete Algorithms for Analysis of Genotype Data |
title_sort |
discrete algorithms for analysis of genotype data |
publisher |
Digital Archive @ GSU |
publishDate |
2007 |
url |
http://digitalarchive.gsu.edu/cs_diss/19 http://digitalarchive.gsu.edu/cgi/viewcontent.cgi?article=1018&context=cs_diss |
work_keys_str_mv |
AT brinzadumitru discretealgorithmsforanalysisofgenotypedata |
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1716583949629652992 |