- Online Mendelian Inheritance in Man (OMIM) is an online catalog of curated
information on human genes and genetic disorders.^69 - Comparative Toxicogenomics Database (CTD) is a database that in addition to
gene-disease relations curated from scientific literature also contains drug—
disease and drug—gene relations.^70 - Functional Disease Ontology (FunDO) is a database containing gene-disease
relations filtered from the Gene Reference Into Function (GeneRIF) database.^71
GeneRIF contains a short description for each gene in the database describing its
function. These descriptions also contain information on the gene’s associations
with disease.
Previous studies of disease classification use projected versions of the gene-
disease bipartite network. For instance, Gohet al.( 2007 ) introduced the first
disease-disease network obtained by projecting the bipartite network onto the
gene partition (two diseases are connected if they have at least one common
gene). However, most integration-based studies analyze the bipartite form of the
gene-disease network, integrated with other biological information.
3.1.7 Drug-Target Interaction (DTI) Bipartite Network
Most drugs act by binding to specific proteins perturbing their molecular activity
and consequently their functions. Drug-target binding can be represented via a
drug-target bipartite interaction network in which a drug and a protein are linked if
the protein is a known target of the drug. Projected representations of this bipartite
network, the drug-drug network and the target-target network, have been a subject
of previous study.^72 However, in data integration studies, the drug-target bipartite
network representation provides a better basis for drug discovery and drug
repositioning.^73
High-quality drug-target interactions can be retrieved from the following data
repositories (Table 1 ):
- DrugBank^74 contains comprehensive information on drugs and drug targets,
including Food and Drug Administration (FDA)-approved small molecule
drugs and experimental drugs. - KEGG BRITE^75 is a reference knowledge database that is an official part of
KEGG database.
(^69) Hamosh et al. ( 2005 ).
(^70) Davis et al. ( 2013 ).
(^71) Osborne et al. ( 2009 ).
(^72) Yildirim et al. ( 2007 ).
(^73) Daminelli et al. ( 2012 ), Wu et al. ( 2013 ), and Yamanishi et al. ( 2008 ).
(^74) Wishart et al. ( 2008 ).
(^75) Kanehisa et al. ( 2006 ).
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