2007
DOI: 10.1093/nar/gkm862
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SuperTarget and Matador: resources for exploring drug-target relationships

Abstract: The molecular basis of drug action is often not well understood. This is partly because the very abundant and diverse information generated in the past decades on drugs is hidden in millions of medical articles or textbooks. Therefore, we developed a one-stop data warehouse, SuperTarget that integrates drug-related information about medical indication areas, adverse drug effects, drug metabolization, pathways and Gene Ontology terms of the target proteins. An easy-to-use query interface enables the user to pos… Show more

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Cited by 526 publications
(408 citation statements)
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“…We focused on the best scoring gene for each drug, obtaining putative novel targets for 307 of the 315 drugs used in this study. To validate these predictions, we compared the predicted associations to those reported in two other sources of drug-target interactions that were not used in the learning process: the Therapeutic Target Database (TTD) (Zhu et al, 2010) and the Matador database (Gunther et al, 2008). TTD included only six interactions that were not part of our original data.…”
Section: Novel Predictionsmentioning
confidence: 99%
See 1 more Smart Citation
“…We focused on the best scoring gene for each drug, obtaining putative novel targets for 307 of the 315 drugs used in this study. To validate these predictions, we compared the predicted associations to those reported in two other sources of drug-target interactions that were not used in the learning process: the Therapeutic Target Database (TTD) (Zhu et al, 2010) and the Matador database (Gunther et al, 2008). TTD included only six interactions that were not part of our original data.…”
Section: Novel Predictionsmentioning
confidence: 99%
“…True drug-target interactions were retrieved from KEGG DRUG (Kanehisa et al, 2010), DrugBank (Wishart et al, 2008), and DCDB (Liu et al, 2010). An independent set of drug-target interactions was downloaded from Matador (Gunther et al, 2008) for validation purposes only. The classification features that we use are constructed from scores calculated on pairs combined of one of M drug-drug measures (five in our case) and one of N gene-gene similarity measures (three in our case), resulting in an MxN set of drug-gene measure features for each drug-target association (15 in our case).…”
Section: Combining Measuresmentioning
confidence: 99%
“…Matador [40] databases and parsing the verified DTIs. This dataset is available in supplementary materials.…”
Section: Methodsmentioning
confidence: 99%
“…At no cost to academics engaged in mental health research, the same group provides experimental compound screening services with a variety of assays, including bioavailability predictions (e.g., CaCo2) and cardiotoxicity (e.g., HERG). SuperTarget (http://insilico.charite.de/supertarget/) provides various views of over 330,000 interactions involving about 6,000 targets and 200,000 compounds, along with annotated pathway diagrams and the ability to browse for targets categorically, such as by function and cellular location 80,81 .…”
Section: Other Small Molecule Databases Ofmentioning
confidence: 99%