TIMMA-R : an R package for predicting synergistic multi-targeted drug combinations in cancer cell lines or patient-derived samples

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dc.contributor.author He, Liye
dc.contributor.author Wennerberg, Krister
dc.contributor.author Aittokallio, Tero
dc.contributor.author Tang, Jing
dc.date.accessioned 2017-10-05T09:04:01Z
dc.date.available 2017-10-05T09:04:01Z
dc.date.issued 2015-06-01
dc.identifier.citation He , L , Wennerberg , K , Aittokallio , T & Tang , J 2015 , ' TIMMA-R : an R package for predicting synergistic multi-targeted drug combinations in cancer cell lines or patient-derived samples ' , Bioinformatics , vol. 31 , no. 11 , pp. 1866-1868 . https://doi.org/10.1093/bioinformatics/btv067
dc.identifier.other PURE: 51841632
dc.identifier.other PURE UUID: 196cdd3d-e155-4237-a04d-d7524f8cefe3
dc.identifier.other WOS: 000356625300030
dc.identifier.other Scopus: 84941656894
dc.identifier.other ORCID: /0000-0002-0886-9769/work/41148387
dc.identifier.other ORCID: /0000-0001-7480-7710/work/40904762
dc.identifier.uri http://hdl.handle.net/10138/225114
dc.description.abstract Network pharmacology-based prediction of multi-targeted drug combinations is becoming a promising strategy to improve anticancer efficacy and safety. We developed a logic-based network algorithm, called Target Inhibition Interaction using Maximization and Minimization Averaging (TIMMA), which predicts the effects of drug combinations based on their binary drug-target interactions and single-drug sensitivity profiles in a given cancer sample. Here, we report the R implementation of the algorithm (TIMMA-R), which is much faster than the original MATLAB code. The major extensions include modeling of multiclass drug-target profiles and network visualization. We also show that the TIMMA-R predictions are robust to the intrinsic noise in the experimental data, thus making it a promising high-throughput tool to prioritize drug combinations in various cancer types for follow-up experimentation or clinical applications. en
dc.format.extent 3
dc.language.iso eng
dc.relation.ispartof Bioinformatics
dc.rights cc_by_nc
dc.rights.uri info:eu-repo/semantics/openAccess
dc.subject DISCOVERY
dc.subject SENSITIVITY
dc.subject RESOURCE
dc.subject 3122 Cancers
dc.subject 1182 Biochemistry, cell and molecular biology
dc.title TIMMA-R : an R package for predicting synergistic multi-targeted drug combinations in cancer cell lines or patient-derived samples en
dc.type Article
dc.contributor.organization Institute for Molecular Medicine Finland
dc.contributor.organization Krister Wennerberg / Principal Investigator
dc.contributor.organization Tero Aittokallio / Principal Investigator
dc.contributor.organization Bioinformatics
dc.description.reviewstatus Peer reviewed
dc.relation.doi https://doi.org/10.1093/bioinformatics/btv067
dc.relation.issn 1367-4803
dc.rights.accesslevel openAccess
dc.type.version publishedVersion

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