Bigram-PGK

Bigram-PGK is a computational tool to predict phosphoglycerylated lysine residues in protein sequences. Phosphoglycerylation is a post-translational modification (PTM) crucial in normal cell biology and disease pathogenesis. Experimental identification of phosphoglycerylation sites is challenging due to cost, time, and efficiency limitations. Bigram-PGK addresses this issue by utilizing evolutionary information of amino acids derived from position-specific scoring matrices (PSSMs) of protein sequences. The tool calculates profile bigram occurrences from PSSMs and employs a support vector machine classifier to predict phosphoglycerylated and non-phosphoglycerylated lysine residues.

Topic

Protein modifications;Small molecules;Proteomics

Detail

  • Operation: Post-translation modification site prediction;PTM localisation;Standardisation and normalisation

  • Software interface: Command-line user interface

  • Language: MATLAB

  • License: Not stated

  • Cost: Free of charge

  • Version name: -

  • Credit: JST CREST, Japan; JSPS KAKENHI, Japan; Nanken-Kyoten, TMDU, Japan.

  • Input: -

  • Output: -

  • Contact: Abel Chandra abelavit@gmail.com ,Alok Sharma alok.sharma@griffith.edu.au

  • Collection: -

  • Maturity: -

Publications

  • Bigram-PGK: phosphoglycerylation prediction using the technique of bigram probabilities of position specific scoring matrix.
  • Chandra A, et al. Bigram-PGK: phosphoglycerylation prediction using the technique of bigram probabilities of position specific scoring matrix. Bigram-PGK: phosphoglycerylation prediction using the technique of bigram probabilities of position specific scoring matrix. 2019; 20:57. doi: 10.1186/s12860-019-0240-1
  • https://doi.org/10.1186/S12860-019-0240-1
  • PMID: 31856704
  • PMC: PMC6923822

Download and documentation

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