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Discovering Complex Relationships between Drugs and Diseases

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Title: Discovering Complex Relationships between Drugs and Diseases
Author: Sharma, Ranjana
Abstract: Finding 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.
Date: -
Subject: Drug development -- Data processing.
Drugs -- Design -- Data processing.
Semantic Web.
Data mining.
Permalink: http://hdl.handle.net/10365/19223

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