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PseKRAAC: a flexible web server for generating pseudo K-tuple reduced amino acids composition
- Source :
- Bioinformatics (Oxford, England). 33(1)
- Publication Year :
- 2016
-
Abstract
- Summary The reduced amino acids perform powerful ability for both simplifying protein complexity and identifying functional conserved regions. However, dealing with different protein problems may need different kinds of cluster methods. Encouraged by the success of pseudo-amino acid composition algorithm, we developed a freely available web server, called PseKRAAC (the pseudo K-tuple reduced amino acids composition). By implementing reduced amino acid alphabets, the protein complexity can be significantly simplified, which leads to decrease chance of overfitting, lower computational handicap and reduce information redundancy. PseKRAAC delivers more capability for protein research by incorporating three crucial parameters that describes protein composition. Users can easily generate many different modes of PseKRAAC tailored to their needs by selecting various reduced amino acids alphabets and other characteristic parameters. It is anticipated that the PseKRAAC web server will become a very useful tool in computational proteomics and protein sequence analysis. Availability and Implementation Freely available on the web at http://bigdata.imu.edu.cn/psekraac Supplementary information Supplementary data are available at Bioinformatics online.
- Subjects :
- 0301 basic medicine
Statistics and Probability
Proteomics
Web server
Theoretical computer science
Computer science
Sequence analysis
computer.software_genre
Biochemistry
03 medical and health sciences
0302 clinical medicine
Software
Protein methods
Sequence Analysis, Protein
Molecular Biology
chemistry.chemical_classification
Internet
Information retrieval
business.industry
Proteins
Protein composition
Computer Science Applications
Amino acid
Computational Mathematics
030104 developmental biology
Computational Theory and Mathematics
chemistry
030220 oncology & carcinogenesis
Tuple
business
computer
Algorithms
Subjects
Details
- ISSN :
- 13674811
- Volume :
- 33
- Issue :
- 1
- Database :
- OpenAIRE
- Journal :
- Bioinformatics (Oxford, England)
- Accession number :
- edsair.doi.dedup.....c2c620d90ed6241e455809e3f1f0244b