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Predicts species-specific lysine acetylation sites based on support vector machine (SVM) classifier. KA-predictor was designed for four species, H. sapiens, M. musculus, E. coli, and S. typhimurium. It employs an efficient feature selection on each type to form the final optimal feature set for model learning. The results indicates that the predictor is highly competitive for the majority of species when compared with other existing methods.

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KA-predictor versioning

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KA-predictor classification

  • Animals
    • Homo sapiens
    • Mus musculus
  • Eubacteria
    • Escherichia coli

KA-predictor specifications

Software type:
Package
Restrictions to use:
None
Input format:
FASTA
Output format:
OUT
Programming languages:
Python
Computer skills:
Advanced
Requirements:
gfortran, python, numpy, tcsh
Interface:
Command line interface
Input data:
A protein sequence file
Output data:
Predicted lysine residue located in the sequence
Operating system:
Unix/Linux, Mac OS
License:
Academic Free License version 3.0
Stability:
Beta

Credits

Publications

  • (Wuyun et al., 2016) Improved Species-Specific Lysine Acetylation Site Prediction Based on a Large Variety of Features Set. PloS One.
    PMID: 27183223

Institution(s)

School of Mathematical Sciences and LPMC, Nankai University, Tianjin, China; Department of Mathematics, School of Science, Hebei University of Engineering, Handan, China; State Key Laboratory of Medicinal Chemical Biology, Nankai University, Tianjin, China

Funding source(s)

This work was supported by NSFC (grant number 11101226) and the Ph.D. Candidate Research Innovation Fund of Nankai University (no. 68150003).

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