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timma (version 1.0.0)

Target Inhibition Interaction using Maximization and Minimization Averaging

Description

Target Inhibition Interaction using Maximization/Minimization Averaging

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Version

Install

install.packages('timma')

Monthly Downloads

14

Version

1.0.0

License

Artistic License 2.0

Maintainer

Liye He

Last Published

December 22nd, 2014

Functions in timma (1.0.0)

miller_drug_response

The single drug does-response data from the Miller study
miller_sensitivity

The scaled drug sensitivity data for the Miller drugs
miller_interaction_binary

The binarized drug-target data for the Miller drugs
sffs

SFFS switch function
searchSpace

Generate search space
sffsCategory1

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

A multi-class drug-target interaction data
sumcpp

Sum for 3D matrix
tyner_interaction_binary

A binary drug-target interaction data
dec2bin

Convert decimal values to binary values
maxcpp1

Search for the max values of 2D matrix in cpp
miller_drugs

A drug list from Miller study
maxcpp

Search for the max values of 3D matrix in cpp
mincpp1

Search for the min values of 2D matrix in cpp
timmaCategory1

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

The curated drug-target data for the Miller drugs
findSameSet

Find the same columns from two matrices
grays

Generate gray code
kiba

Kiba interaction data
sffsBinary1

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

The drug sensitivity data
timmaSearchBinary1

Prediction in the search space with two.sided TIMMA model
sffsBinary2

Model selection with filtered binary drug-target interaction data
timma

Main function for the timma package
floating2

Filter targets
sumcpp1

Sum for 2D matrix in cpp
drugRank

Generate the list of ranked drug combinations
graycode3

Gray code function for matrix indexes
timmaModel1

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

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

Predicting drug sensitivity with binary drug-target interaction data
sffsCategoryWeighted

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

Prediction in the search space with one.sided TIMMA model
getBinary

Binary set for multiclass data
timmaCategoryWeighted

Predicting drug sensitivity with multi-class drug-target interaction data using one.sided and weighted TIMMA model
graycode2

Graycode Function
timmaBinary

Predicting drug sensitivity with binary drug-target interaction data
timmaCategoryWeighted1

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

The combination index extracted from Figure 1B of the Miller study
getBinary1

Weighted binary set for multiclass data
mincpp

Search for the min values of 3D matrix in cpp
sffsBinary

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

Search for supersets and subsets
timmaBinary1

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

Predicting drug sensitivity with multi-class drug-target interaction data using one.sided TIMMA model
sffsCategoryWeighted1

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

Target Inhibition inference using Maximization and Minimization Averaging
drawGraph

Draw graph function
findSameCol

Find the same column from a matrix
graycodeNames

Names for the predicted sensitivity matrix