<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>15</volume><submitter>Roider HG</submitter><pubmed_abstract>&lt;h4>Background&lt;/h4>Information about drug-target relations is at the heart of drug discovery. There are now dozens of databases providing drug-target interaction data with varying scope, and focus. Therefore, and due to the large chemical space, the overlap of the different data sets is surprisingly small. As searching through these sources manually is cumbersome, time-consuming and error-prone, integrating all the data is highly desirable. Despite a few attempts, integration has been hampered by the diversity of descriptions of compounds, and by the fact that the reported activity values, coming from different data sets, are not always directly comparable due to usage of different metrics or data formats.&lt;h4>Description&lt;/h4>We have built Drug2Gene, a knowledge base, which combines the com</pubmed_abstract><journal>BMC bioinformatics</journal><pagination>68</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC4234465</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>Drug2Gene: an exhaustive resource to explore effectively the drug-target relation network.</pubmed_title><pmcid>PMC4234465</pmcid><pubmed_authors>Slavov T</pubmed_authors><pubmed_authors>Pavlova N</pubmed_authors><pubmed_authors>Slavov S</pubmed_authors><pubmed_authors>Weiss B</pubmed_authors><pubmed_authors>Uzunov Z</pubmed_authors><pubmed_authors>Roider HG</pubmed_authors><pubmed_authors>Kirov I</pubmed_authors></additional><is_claimable>false</is_claimable><name>Drug2Gene: an exhaustive resource to explore effectively the drug-target relation network.</name><description>&lt;h4>Background&lt;/h4>Information about drug-target relations is at the heart of drug discovery. There are now dozens of databases providing drug-target interaction data with varying scope, and focus. Therefore, and due to the large chemical space, the overlap of the different data sets is surprisingly small. As searching through these sources manually is cumbersome, time-consuming and error-prone, integrating all the data is highly desirable. Despite a few attempts, integration has been hampered by the diversity of descriptions of compounds, and by the fact that the reported activity values, coming from different data sets, are not always directly comparable due to usage of different metrics or data formats.&lt;h4>Description&lt;/h4>We have built Drug2Gene, a knowledge base, which combines the com</description><dates><release>2014-01-01T00:00:00Z</release><publication>2014 Mar</publication><modification>2025-04-26T20:10:20.716Z</modification><creation>2019-03-27T01:39:45Z</creation></dates><accession>S-EPMC4234465</accession><cross_references><pubmed>24618344</pubmed><doi>10.1186/1471-2105-15-68</doi></cross_references></HashMap>