ArticleBMC bioinformatics2008
Predikin and PredikinDB: a computational framework for the prediction of protein kinase peptide specificity and an associated database of phosphorylation sites.
Article in BMC bioinformatics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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24 citing papers in PubMed, 64 citations in OpenAlex.
- Deep Learning in Phosphoproteomics: Methods and Application in Cancer Drug Discovery.Proteomes · 2023Review
- A Proteome-Wide Immunoinformatics Tool to Accelerate T-Cell Epitope Discovery and Vaccine Design in the Context of Emerging Infectious Diseases: An Ethnicity-Oriented Approach.Frontiers in immunology · 2021Article
- DeepKinZero: zero-shot learning for predicting kinase-phosphosite associations involving understudied kinases.Bioinformatics (Oxford, England) · 2020Article
- Exploring protein phosphorylation by combining computational approaches and biochemical methods.Computational and structural biotechnology journal · 2020Article
- Using phosphoproteomics data to understand cellular signaling: a comprehensive guide to bioinformatics resources.Clinical proteomics · 2020Review
- MoMo: discovery of statistically significant post-translational modification motifs.Bioinformatics (Oxford, England) · 2019Article
- In Silico Design and in Vitro Characterization of Universal Tyrosine Kinase Peptide Substrates.Biochemistry · 2018Article
- Article
- Navigating the multilayered organization of eukaryotic signaling: a new trend in data integration.PLoS computational biology · 2014Review
- Dynamics of re-constitution of the human nuclear proteome after cell division is regulated by NLS-adjacent phosphorylation.Cell cycle (Georgetown, Tex.) · 2014Article
- Exploiting holistic approaches to model specificity in protein phosphorylation.Frontiers in genetics · 2014Review
- The coming of age of phosphoproteomics--from large data sets to inference of protein functions.Molecular & cellular proteomics : MCP · 2013Review
- PREDIVAC: CD4+ T-cell epitope prediction for vaccine design that covers 95% of HLA class II DR protein diversity.BMC bioinformatics · 2013Article
- The importance of conserved features of yeast actin-binding protein 1 (Abp1p): the conditional nature of essentiality.Genetics · 2012Article
- PhosTryp: a phosphorylation site predictor specific for parasitic protozoa of the family trypanosomatidae.BMC genomics · 2011Article
- Deciphering the Arginine-binding preferences at the substrate-binding groove of Ser/Thr kinases by computational surface mapping.PLoS computational biology · 2011Article
- Prediction of 492 human protein kinase substrate specificities.Proteome science · 2011Article
- Predicting protein kinase specificity: Predikin update and performance in the DREAM4 challenge.PloS one · 2011Article
- The Musite open-source framework for phosphorylation-site prediction.BMC bioinformatics · 2010Article
- Musite, a tool for global prediction of general and kinase-specific phosphorylation sites.Molecular & cellular proteomics : MCP · 2010Article
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundWe have previously described an approach to predicting the substrate specificity of serine-threonine protein kinases. The method, named Predikin, identifies key conserved substrate-determining residues in the kinase catalytic domain that contact the substrate in the region of the phosphorylation site and so determine the sequence surrounding the phosphorylation site. Predikin was implemented originally as a web application written in Javascript.
resultsHere, we describe a new version of Predikin, completely revised and rewritten as a modular framework that provides multiple enhancements compared with the original. Predikin now consists of two components: (i) PredikinDB, a database of phosphorylation sites that links substrates to kinase sequences and (ii) a Perl module, which provides methods to classify protein kinases, reliably identify substrate-determining residues, generate scoring matrices and score putative phosphorylation sites in query sequences. The performance of Predikin as measured using receiver operator characteristic (ROC) graph analysis equals or surpasses that of existing comparable methods. The Predikin website has been redesigned to incorporate the new features.
conclusionNew features in Predikin include the use of SQL queries to PredikinDB to generate predictions, scoring of predictions, more reliable identification of substrate-determining residues and putative phosphorylation sites, extended options to handle protein kinase and substrate data and an improved web interface. The new features significantly enhance the ability of Predikin to analyse protein kinases and their substrates. Predikin is available at http://predikin.biosci.uq.edu.au.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.