TIMMA-R: an R package for predicting synergistic multi-targeted drug combinations in cancer cell lines or patient-derived samples
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
UNLABELLED: 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.
AVAILABILITY AND IMPLEMENTATION: TIMMA-R source code is freely available at http://cran.r-project.org/web/packages/timma/.
Originalsprog | Engelsk |
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Tidsskrift | Bioinformatics (Online) |
Vol/bind | 31 |
Udgave nummer | 11 |
Sider (fra-til) | 1866-8 |
Antal sider | 3 |
ISSN | 1367-4811 |
DOI | |
Status | Udgivet - 1 jun. 2015 |
Eksternt udgivet | Ja |
ID: 199429384