kfold.MATCH: MATCH training process
In MEET: MEET: Motif Elements Estimation Toolkit

Description Usage Arguments Value Author(s) References See Also Examples

For a vector of Core cut values this function calculates returns a matrix of Similarities and labels indicating if a sequence position is a binding site or not. To calculate the Similartiy a leave-one-out cross training model is used. With the utput of this function a ROC curve can be calculated for each Core Similarity and the results can be compared.

1	kfold.MATCH(iicc, Seqin)

`iicc`	List of options described in the MEET program
`Seqin`	DNA sequence

For each num

Erola Pairo <epairo@ibecbarcelona.eu>

A.E. Kel , E. Gossling , I. Reuter , E. Cheremushkin , O.V. Kel-Margoulis , and E. Wingender MATCHTM: a tool for searching transcription factor binding sites in DNA sequences Nucl. Acids Res. 31: 3576.

Match, MEET

data(iicc)
data(TranscriptionFactor)
iicc$method<-"MATCH"

iicc$vector<-c(0.5, 0.8)
library(seqinr)
#writing sequences to model in fasta format
write.fasta <- get("write.fasta",pos="package:seqinr")
write.fasta(sequences=TranscriptionFactor,names=c(1:length(TranscriptionFactor)),file.out="Sq.fa",open="w") 
kfold.MATCH(iicc, "Sq.fa")