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Center of Excellence In Genomic Medicine Research
Document Details
Document Type
:
Article In Journal
Document Title
:
repDNA: a Python package to generate various modes of feature vectors for DNA sequences by incorporating user-defined physicochemical properties and sequence-order effects
repDNA: a Python package to generate various modes of feature vectors for DNA sequences by incorporating user-defined physicochemical properties and sequence-order effects
Document Language
:
English
Abstract
:
In order to develop powerful computational predictors for identifying the biological features or attributes of DNAs, one of the most challenging problems is to find a suitable approach to effectively represent the DNA sequences. To facilitate the studies of DNAs and nucleotides, we developed a Python package called representations of DNAs (repDNA) for generating the widely used features reflecting the physicochemical properties and sequence-order effects of DNAs and nucleotides. There are three feature groups composed of 15 features. The first group calculates three nucleic acid composition features describing the local sequence information by means of kmers; the second group calculates six autocorrelation features describing the level of correlation between two oligonucleotides along a DNA sequence in terms of their specific physicochemical properties; the third group calculates six pseudo nucleotide composition features, which can be used to represent a DNA sequence with a discrete model or vector yet still keep considerable sequence-order information via the physicochemical properties of its constituent oligonucleotides. In addition, these features can be easily calculated based on both the built-in and user-defined properties via using repDNA.
ISSN
:
1367-4811
Journal Name
:
Bioinformatics
Volume
:
31
Issue Number
:
8
Publishing Year
:
1436 AH
2015 AD
Article Type
:
Article
Added Date
:
Sunday, April 24, 2016
Researchers
Researcher Name (Arabic)
Researcher Name (English)
Researcher Type
Dr Grade
Email
Bin Liu
Liu, Bin
Investigator
Fule Liu
Liu, Fule
Researcher
Longyun Fang
Fang, Longyun
Researcher
Xiaolong Wang
Wang, Xiaolong
Researcher
Kuo-Chen Chou
Chou, Kuo-Chen
Researcher
Files
File Name
Type
Description
38659.pdf
pdf
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