Description Details Author(s) References Examples
Due to the exponentially increasing number of potential drug and target combinations, it is meaningful to select the most promising combinations based on computational models. The TIMMA model was proposed to utilize drug-target interaction data and drug sensitivity data to infer the effects of drug combinations. This R package TIMMA is the implementation of the TIMMA model. It consists of the following components: (a) model selection using the sffs algorithm; (b) model construction using the maximization and minimization averaging rules; (c) ranking of drug combinations according to their synergy scores and a target inhibition network.
Package: | TIMMA |
Type: | Package |
Version: | 0.99.0 |
Date: | 2014-10-07 |
License: | Artistic License 2.0 |
Liye He liye.he@helsinki.fi
Tang J, Karhinen L, Xu T, Szwajda A, Yadav B, Wennerberg K, Aittokallio T. Target inhibition networks: predicting selective combinations of druggable targets to block cancer survival pathways. PLOS Computational Biology 2013; 9: e1003226.
1 2 3 4 5 6 7 | ## Not run:
data(tyner_interaction_binary)
data(tyner_sensitivity)
median_sensitivity<-tyner_sensitivity[, 1]
results<-timma(tyner_interaction_binary, median_sensitivity)
## End(Not run)
|
----------------Start Running TIMMA-----------------------------
----------------Complete running TIMMA model--------------------
----------------Saving selectedTargets.csv----------------------
----------------Saving predictedSensitivities.csv---------------
----------------Saving predictedTargetScoring.csv---------------------
----------------Saving predictedDrugScoring.csv---------------------
----------------Saving result.RData----------------------
----------------Saving targetInhibitionNetwork.pdf--------------
----------------Saving targetInhibitionNetwork.nnf--------------
Analysis finished. All the results are saved in /work/tmpWarning: stack imbalance in '<-', 2 then 3
Warning message:
Function eqmcc() is deprecated, and has been renamed to minimize()
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