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timma (version 1.2.1)

Target Inhibition Interaction using Maximization and Minimization Averaging

Description

Prediction and ranking of drug combinations based on their drug-target interaction profiles and single-drug sensitivities in a given cancer cell line or patient-derived sample.

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Version

Install

install.packages('timma')

Monthly Downloads

14

Version

1.2.1

License

Artistic License 2.0

Maintainer

Jing Tang

Last Published

February 28th, 2015

Functions in timma (1.2.1)

Search for the min values of 3D matrix in cpp

binarizeDrugTargets

Binarize the drug target profile data

Convert decimal values to binary values

sffsCategoryWeighted

Model selection with sffs for the multi-class drug-target interaction data using one.sided and weighted TIMMA model

sffsCategoryWeighted1

Model selection with sffs for the multi-class drug-target interaction data using two.sided and weighted TIMMA model

Gray code function for matrix indexes

Search for the min values of 2D matrix in cpp

The curated drug-target data for the Miller drugs

Find the same column from a matrix

Find the same columns from two matrices

timmaCategoryWeighted

Predicting drug sensitivity with multi-class drug-target interaction data using one.sided and weighted TIMMA model

Predicting drug sensitivity with binary drug-target interaction data

timmaSearchBinary1

Prediction in the search space with two.sided TIMMA model

Generate search space

Kiba interaction data

The combination index extracted from Figure 1B of the Miller study

tyner_interaction_binary

A binary drug-target interaction data

Target Inhibition inference using Maximization and Minimization Averaging

timmaCategoryWeighted1

Predicting drug sensitivity with multi-class drug-target interaction data using two.sided and weighted TIMMA model

miller_sensitivity

The scaled drug sensitivity data for the Miller drugs

Predicting drug sensitivity with binary drug-target interaction data using modified maximization and minimization rules

timmaSearchBinary

Prediction in the search space with one.sided TIMMA model

Model selection with sffs for the binary drug-target interaction data using two.sided TIMMA model

Draw graph function

Graycode Function

miller_interaction_binary

The binarized drug-target data for the Miller drugs

Model selection with sffs for the multi-class drug-target interaction data using two.sided TIMMA model

Predicting drug sensitivity with multi-class drug-target interaction data using one.sided TIMMA model

Model selection with filtered binary drug-target interaction data

Main function for the timma package

miller_drug_response

The single drug does-response data from the Miller study

Model selection with sffs for the multi-class drug-target interaction data using one.sided TIMMA model

Generate the list of ranked drug combinations

Drug-target profile for 72 drugs and 442 targets.

Binary set for multiclass data

Weighted binary set for multiclass data

Search for the max values of 2D matrix in cpp

SFFS switch function

Predicting drug sensitivity with multi-class drug-target interaction data using two.sided TIMMA model

Sum for 2D matrix in cpp

Model selection with sffs for the binary drug-target interaction data

Predicting drug sensitivity with binary drug-target interaction data using two.sided TIMMA model

Sum for 3D matrix

Generate gray code

Generate the list of ranked target combinations

Predicting drug sensitivity with binary drug-target interaction data

tyner_sensitivity

The drug sensitivity data

normalizeSensitivity

Normalize the drug sensitivity data

Names for the predicted sensitivity matrix

tyner_interaction_multiclass

A multi-class drug-target interaction data

Search for supersets and subsets

Search for the max values of 3D matrix in cpp

A drug list from Miller study