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Bioinformatics. 2019 Jul 18. pii: btz568. doi: 10.1093/bioinformatics/btz568. [Epub ahead of print]

PTM-Logo: a program for generation of sequence logos based on position-specific background amino-acid probabilities.

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Center of Excellence in Systems Biology, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand.
Department of Computer Science, Kasetsart University, Bangkok, Thailand.
Epithelial Systems Biology Laboratory, NHLBI, National Institutes of Health, Bethesda, MD, USA.
Department of Microbiology, Faculty of Science, Kasetsart University, Bangkok, Thailand.



Identification of the amino-acid motifs in proteins that are targeted for post-translational modifications (PTMs) is of great importance in understanding regulatory networks. Information about targeted motifs can be derived from mass spectrometry data that identify peptides containing specific PTMs such as phosphorylation, ubiquitylation, and acetylation. Comparison of input data against a standardized "background" set allows identification of over- and under-represented amino acids surrounding the modified site. Conventionally, calculation of targeted motifs assumes a random background distribution of amino acids surrounding the modified position. However, we show that probabilities of amino acids depend on 1) the type of the modification and 2) their positions relative to the modified site. Thus, software that identifies such over- and under-represented amino acids should make appropriate adjustments for these effects. Here we present a new program, PTM-Logo, that generates representations of these amino acid preferences ("logos") based on position-specific amino-acid probability backgrounds calculated either from user-input data or curated databases.


PTM-Logo is freely available online at or (temporary password = reviewer).


Supplementary data are available at Bioinformatics online.

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