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

• DOI: 10.18632/oncotarget.14524
• Publication Date: 2017-01-08T15:05:47Z
• Authors: Bin Liu; Hao Wu; Deyuan Zhang; Xiaolong Wang; Kuo-Chen Chou
• Keywords: 0303 health sciences; 03 medical and health sciences; Support Vector Machine; Animals; Computational Biology; Humans; Sequence Analysis; Software; Research Paper

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.