Towards constructing disease relationship networks using genome-wide association studies

Simple item page
dc.contributor.authorHuang, Wenhuien
dc.contributor.committeechairZhang, Liqingen
dc.contributor.committeememberLi, Liwuen
dc.contributor.committeememberFan, Weiguo Patricken
dc.contributor.departmentComputer Scienceen
dc.date.accessioned2014-03-14T21:52:07Zen
dc.date.adate2010-01-19en
dc.date.available2014-03-14T21:52:07Zen
dc.date.issued2009-12-07en
dc.date.rdate2010-01-19en
dc.date.sdate2009-12-21en
dc.description.abstractBackground: Genome-wide association studies (GWAS) prove to be a powerful approach to identify the genetic basis of various human[1] diseases. Here we take advantage of existing GWAS data and attempt to build a framework to understand the complex relationships among diseases. Specifically, we examined 49 diseases from all available GWAS with a cascade approach by exploiting network analysis to study the single nucleotide polymorphisms (SNP) effect on the similarity between different diseases. Proteins within perturbation subnetwork are considered to be connection points between the disease similarity networks. Results: shared disease subnetwork proteins are consistent, accurate and sensitive to measure genetic similarity between diseases. Clustering result shows the evidence of phenome similarity. Conclusion: our results prove the usefulness of genetic profiles for evaluating disease similarity and constructing disease relationship networks.en
dc.description.degreeMaster of Scienceen
dc.identifier.otheretd-12212009-174030en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-12212009-174030/en
dc.identifier.urihttp://hdl.handle.net/10919/46326en
dc.publisherVirginia Techen
dc.relation.haspartHuang_W_T_2009.pdfen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectDiseaseRelationshipen
dc.subjectNetworken
dc.subjectGWASen
dc.subjectSNPen
dc.subjectProtein-Protein Interactionen
dc.titleTowards constructing disease relationship networks using genome-wide association studiesen
dc.typeThesisen
thesis.degree.disciplineComputer Scienceen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Huang_W_T_2009.pdf
Size:
274.12 KB
Format:
Adobe Portable Document Format
Download

Collections

Masters Theses