Data-driven analysis of genomic factors and gene expression for neurological disorder study = 뇌질환 연구를 위한 데이터 주도적 유전적 인자와 유전자 발현 분석

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dc.contributor.advisorLee, Do-Heon-
dc.contributor.advisor이도헌-
dc.contributor.authorPark, Young-Kyu-
dc.contributor.author박영규-
dc.date.accessioned2015-04-23T02:10:20Z-
dc.date.available2015-04-23T02:10:20Z-
dc.date.issued2014-
dc.identifier.urihttp://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=568473&flag=dissertation-
dc.identifier.urihttp://hdl.handle.net/10203/196348-
dc.description학위논문(박사) - 한국과학기술원 : 바이오및뇌공학과, 2014.2, [ viii, 92 p. ]-
dc.description.abstractA neurological disorder is a disease of the body nervous system caused from the structural, biochemical or electrical abnormalities in the brain, spinal cord or other nerves. It comprises brain diseases including cerebrovascular disease, a heterogeneous complex disease from the interaction between various genetic and environmental risk factors, and Parkinson’s disease, a neurodegenerative disease caused by the death of the brain cells producing dopamine molecules. To understand the underlying molecular mechanisms of neurological disorder progression and treatment, the genomic and epigenomic basis of the disease must be analyzed collectively in terms of biological function and pathway relationships. To this end, an efficient bioinformatics tools including database system integrating genetic variants and related annotation, and other informatics tools to help experimental studies or data analysis are indispensable. In this research, I conducted three bioinformatics approaches to help and contribute to the studies on the genetic and pathological mechanisms of neurological disorders in terms of the genomics, functional genomics and epigenomics layers.First, in terms of genomics for neurological disorder study, I developed SigCS base, an integrative genetic information database for human cerebrovascular disease. The genetic variants, annotations, and bibliographical information of cerebrovascular disease and its etiologies were extracted from the public resources, integrated in terms of biological function and pathway relationships, and stored into the relational database with efficient retrieval system. SigCS base allows researchers studying the mechanisms of cerebral stroke to evaluate thousands of genomic variants and genes associated with stroke and its etiologies, as well as relevant annotations. Researchers can also select candidate genes or variants for their studies, compare their genetic factors with previously reported results, and examine the pathways co...eng
dc.languageeng-
dc.publisher한국과학기술원-
dc.subjectneurological disorders-
dc.subjectDNA수산화메틸화-
dc.subjectDNA 메틸화-
dc.subjectsiRNA-
dc.subject데이터베이스-
dc.subject유전자 발현-
dc.subjectgenetic variants-
dc.subjectgene expression-
dc.subjectdatabase-
dc.subjectsiRNA-
dc.subjectDNA methylation-
dc.subjectDNA hydroxymethylation-
dc.subject뇌질환-
dc.subject유전변이-
dc.titleData-driven analysis of genomic factors and gene expression for neurological disorder study = 뇌질환 연구를 위한 데이터 주도적 유전적 인자와 유전자 발현 분석-
dc.typeThesis(Ph.D)-
dc.identifier.CNRN568473/325007 -
dc.description.department한국과학기술원 : 바이오및뇌공학과, -
dc.identifier.uid020075280-
dc.contributor.localauthorLee, Do-Heon-
dc.contributor.localauthor이도헌-
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