TY - JOUR
T1 - Pse-Analysis
T2 - A python package for DNA/RNA and protein/ peptide sequence analysis based on pseudo components and kernel methods
AU - Liu, Bin
AU - Wu, Hao
AU - Zhang, Deyuan
AU - Wang, Xiaolong
AU - Chou, Kuo Chen
PY - 2017
Y1 - 2017
N2 - 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.
AB - 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.
KW - Genome/proteome analysis
KW - Pseudo components
KW - Sequence analysis
KW - Support vector machine
UR - https://www.scopus.com/pages/publications/85013243690
U2 - 10.18632/oncotarget.14524
DO - 10.18632/oncotarget.14524
M3 - Article
C2 - 28076851
AN - SCOPUS:85013243690
SN - 1949-2553
VL - 8
SP - 13338
EP - 13343
JO - Oncotarget
JF - Oncotarget
IS - 8
ER -