Predicting promoters by pseudo-trinucleotide compositions based on discrete wavelets transform.
about
PseKNC-General: a cross-platform package for generating various modes of pseudo nucleotide compositions.Assessing the effects of data selection and representation on the development of reliable E. coli sigma 70 promoter region predictors.iPro54-PseKNC: a sequence-based predictor for identifying sigma-54 promoters in prokaryote with pseudo k-tuple nucleotide composition.repDNA: a Python package to generate various modes of feature vectors for DNA sequences by incorporating user-defined physicochemical properties and sequence-order effects.Prediction of aptamer-protein interacting pairs using an ensemble classifier in combination with various protein sequence attributesPseudo nucleotide composition or PseKNC: an effective formulation for analyzing genomic sequences.70ProPred: a predictor for discovering sigma70 promoters based on combining multiple features.Prediction of DNase I hypersensitive sites by using pseudo nucleotide compositions.
P2860
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P2860
Predicting promoters by pseudo-trinucleotide compositions based on discrete wavelets transform.
description
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name
Predicting promoters by pseudo ...... n discrete wavelets transform.
@en
Predicting promoters by pseudo ...... n discrete wavelets transform.
@nl
type
label
Predicting promoters by pseudo ...... n discrete wavelets transform.
@en
Predicting promoters by pseudo ...... n discrete wavelets transform.
@nl
prefLabel
Predicting promoters by pseudo ...... n discrete wavelets transform.
@en
Predicting promoters by pseudo ...... n discrete wavelets transform.
@nl
P2093
P1476
Predicting promoters by pseudo ...... n discrete wavelets transform.
@en
P2093
Xiaoyong Zou
Zhanchao Li
P356
10.1016/J.JTBI.2012.11.024
P407
P577
2012-12-02T00:00:00Z