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Pse-Analysis: A python package for DNA/RNA and protein/ peptide sequence analysis based on pseudo components and kernel methods

  • Bin Liu*
  • , Hao Wu
  • , Deyuan Zhang
  • , Xiaolong Wang
  • , Kuo Chen Chou
  • *Corresponding author for this work
  • Harbin Institute of Technology
  • Harbin Institute of Technology Shenzhen
  • Gordon Life Science Institute
  • Shenyang Aerospace University
  • University of Electronic Science and Technology of China

Research output: Contribution to journalArticlepeer-review

Abstract

To expedite the pace in conducting genome/proteome analysis, we have developed a Python package called Pse-Analysis. The powerful package can automatically complete the following five procedures: (1) sample feature extraction, (2) optimal parameter selection, (3) model training, (4) cross validation, and (5) evaluating prediction quality. All the work a user needs to do is to input a benchmark dataset along with the query biological sequences concerned. Based on the benchmark dataset, Pse-Analysis will automatically construct an ideal predictor, followed by yielding the predicted results for the submitted query samples. All the aforementioned tedious jobs can be automatically done by the computer. Moreover, the multiprocessing technique was adopted to enhance computational speed by about 6 folds. The Pse-Analysis Python package is freely accessible to the public at http://bioinformatics.hitsz.edu.cn/Pse-Analysis/, and can be directly run on Windows, Linux, and Unix.

Original languageEnglish
Pages (from-to)13338-13343
Number of pages6
JournalOncotarget
Volume8
Issue number8
DOIs
Publication statusPublished - 2017
Externally publishedYes

Keywords

  • Genome/proteome analysis
  • Pseudo components
  • Sequence analysis
  • Support vector machine

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