title: TIMMA-R: an R package for predicting synergistic multi-targeted drug combinations in cancer cell lines or patient-derived samples.
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.
  
  
  METHODS
  TIMMA-R source code is freely available at http://cran.r-project.org/web/packages/timma/.
authors: Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Tukholmankatu 8, FI-00290, Helsinki, Finland.
authors: Liye
authors: L
authors: He
authors: Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Tukholmankatu 8, FI-00290, Helsinki, Finland.
authors: Krister
authors: K
authors: Wennerberg
authors: Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Tukholmankatu 8, FI-00290, Helsinki, Finland.
authors: Tero
authors: T
authors: Aittokallio
authors: Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Tukholmankatu 8, FI-00290, Helsinki, Finland.
authors: Jing
authors: J
authors: Tang
mesh_terms: D000465:Algorithms; D000971:Antineoplastic Combined Chemotherapy Protocols / Q000494:pharmacology*; D045744:Cell Line, Tumor; D055808:Drug Discovery; D004357:Drug Synergism; D006801:Humans; D009369:Neoplasms / Q000188:drug therapy; D012984:Software
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