iSuc-PseOpt specifications


Unique identifier OMICS_11163
Name iSuc-PseOpt
Interface Web user interface
Restrictions to use None
Input data Protein sequence(s)
Input format FASTA
Computer skills Basic
Stability Stable
Maintained Yes


  • person_outline Xuan Xiao <>

Publication for iSuc-PseOpt

iSuc-PseOpt in publications

PMCID: 5809022
PMID: 29432431
DOI: 10.1371/journal.pone.0191900

[…] into the general form of pseudo amino acid composition for training a support vector machine []. another method that incorporates sequence-coupling effects into the pseudo amino acid composition was isuc-pseopt []. it introduced the k-nearest neighbors strategy and hypothetical training samples in an attempt to ameliorate the imbalance between classes. subsequently, a random forest algorithm […]

PMCID: 5584904
PMID: 28894368
DOI: 10.2147/IJN.S140875

[…] succinsite, in which the three informative sequence encoding features, that is, cksaap, binary, and the selected aaindex physicochemical features, were combined. recently, jia et al developed the isuc-pseopt predictor, based on pseudo amino acid composition encoding with k-nearest neighbors’ algorithm. meanwhile, jia et al developed psuc-lys based on a pseudo amino acid composition encoding […]

To access a full list of publications, you will need to upgrade to our premium service.

iSuc-PseOpt institution(s)
Computer Department, Jing-De-Zhen Ceramic Institute, Jing-De-Zhen, China; Gordon Life Science Institute, Boston, MA, USA; Center of Excellence in Genomic Medicine Research (CEGMR), King Abdulaziz University, Jeddah, Saudi Arabia
iSuc-PseOpt funding source(s)
This work was partially supported by the National Nature Science Foundation of China (61261027, 31260273, 31560316, and 31560316), the Natural Science Foundation of Jiangxi Province (20122BAB211033, 20122BAB201044, and 20132BAB201053), and the Scientific Research plan of the Department of Education of Jiangxi Province (GJJ14640).

iSuc-PseOpt reviews

star_border star_border star_border star_border star_border
star star star star star

Be the first to review iSuc-PseOpt