ArticleBioinformatics (Oxford, England)2019
PTM-Logo: a program for generation of sequence logos based on position-specific background amino-acid probabilities.
Article in Bioinformatics (Oxford, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Phosphoproteomic response to epidermal growth factor in native rat inner medullary collecting duct.American journal of physiology. Renal physiology · 2025Article
- Analysis of phosphomotifs coupled to phosphoproteome and interactome unveils potential human kinase substrate proteins in SARS-CoV-2.Frontiers in cellular and infection microbiology · 2025Article
- Bayesian mapping of protein kinases to vasopressin-regulated phosphorylation sites in renal collecting duct.American journal of physiology. Renal physiology · 2024Article
- A resource database for protein kinase substrate sequence-preference motifs based on large-scale mass spectrometry data.Cell communication and signaling : CCS · 2024Article
- Using CRISPR-Cas9/phosphoproteomics to identify substrates of calcium/calmodulin-dependent kinase 2δ.The Journal of biological chemistry · 2023Article
- Bayesian analysis of dynamic phosphoproteomic data identifies protein kinases mediating GPCR responses.Cell communication and signaling : CCS · 2022Article
- Integrated Phosphoproteomics for Identifying Substrates of Human Protein Kinase A (Journal of proteome research · 2021Article
- Phosphoproteomic identification of vasopressin-regulated protein kinases in collecting duct cells.British journal of pharmacology · 2021Article
- iDPGK: characterization and identification of lysine phosphoglycerylation sites based on sequence-based features.BMC bioinformatics · 2020Article
- PKA-independent vasopressin signaling in renal collecting duct.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2020Article
- dagLogo: An R/Bioconductor package for identifying and visualizing differential amino acid group usage in proteomics data.PloS one · 2020Article
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7 authors.
Funding
Abstract
summaryIdentification 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 (i) the type of the modification and (ii) 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. AVAILABILITY AND IMPLEMENTATION: PTM-Logo is freely available online at http://sysbio.chula.ac.th/PTMLogo/ or https://hpcwebapps.cit.nih.gov/PTMLogo/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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