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dc.contributor.authorSharma, Ranjana
dc.description.abstractFinding the complex semantic relations between existing drugs and new diseases will help in the drug development in a new way. Most of the drugs which have found new uses have been discovered due to serendipity. Hence, the prediction of the uses of drugs for more than one disease should be done in a systematic way by studying the semantic relations between the drugs and diseases and also the other entities involved in the relations. Hence, in order to study the complex semantic relations between drugs and diseases an application was developed that integrates the heterogeneous data in different formats from different public databases which are available online. A high level ontology was also developed to integrate the data and only the fields required for the current study were used. The data was collected from different data sources such as DrugBank, UniProt/SwissProt, GeneCards and OMIM. Most of these data sources are the standard data sources and have been used by National Committee of Biotechnology Information of Nation Institute of Health. The data was parsed and integrated and complex semantic relations were discovered. This is a simple and novel effort which may find uses in development of new drug targets and polypharmacology.
dc.publisherNorth Dakota State Universityen_US
dc.rightsNDSU Policy 190.6.2
dc.titleDiscovering Complex Relationships between Drugs and Diseasesen_US
dc.typeMaster's paperen_US
dc.date.accessioned2012-01-26T19:29:17Z
dc.date.available2012-01-26T19:29:17Z
dc.date.issued2011
dc.identifier.urihttp://hdl.handle.net/10365/19223
dc.subject.lcshDrug development -- Data processing.en_US
dc.subject.lcshDrugs -- Design -- Data processing.en_US
dc.subject.lcshSemantic Web.en_US
dc.subject.lcshData mining.en_US
dc.rights.urihttps://www.ndsu.edu/fileadmin/policy/190.pdf
ndsu.degreeMaster of Science (MS)en_US
ndsu.collegeEngineeringen_US
ndsu.departmentComputer Scienceen_US
ndsu.programComputer Scienceen_US
ndsu.advisorLi, Juan


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