{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Xue B"],"funding":["National Cancer Institute","NCI NIH HHS"],"pagination":["e1008681"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC7895412"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["17(2)"],"pubmed_abstract":["Tyrosine and serine/threonine kinases are essential regulators of cell processes and are important targets for human therapies. Unfortunately, very little is known about specific kinase-substrate relationships, making it difficult to infer meaning from dysregulated phosphoproteomic datasets or for researchers to identify possible kinases that regulate specific or novel phosphorylation sites. The last two decades have seen an explosion in algorithms to extrapolate from what little is known into the larger unknown-predicting kinase relationships with site-specific substrates using a variety of approaches that include the sequence-specificity of kinase catalytic domains and various other factors, such as evolutionary relationships, co-expression, and protein-protein interaction networks. Unfo"],"journal":["PLoS computational biology"],"pubmed_title":["KinPred: A unified and sustainable approach for harnessing proteome-level human kinase-substrate predictions."],"pmcid":["PMC7895412"],"funding_grant_id":["R21 CA231853","R21CA231853"],"pubmed_authors":["Naegle KM","Rizvi S","Xue B","Jordan B"],"additional_accession":[]},"is_claimable":false,"name":"KinPred: A unified and sustainable approach for harnessing proteome-level human kinase-substrate predictions.","description":"Tyrosine and serine/threonine kinases are essential regulators of cell processes and are important targets for human therapies. Unfortunately, very little is known about specific kinase-substrate relationships, making it difficult to infer meaning from dysregulated phosphoproteomic datasets or for researchers to identify possible kinases that regulate specific or novel phosphorylation sites. The last two decades have seen an explosion in algorithms to extrapolate from what little is known into the larger unknown-predicting kinase relationships with site-specific substrates using a variety of approaches that include the sequence-specificity of kinase catalytic domains and various other factors, such as evolutionary relationships, co-expression, and protein-protein interaction networks. Unfo","dates":{"release":"2021-01-01T00:00:00Z","publication":"2021 Feb","modification":"2026-05-09T10:59:41.601Z","creation":"2021-03-05T09:05:00Z"},"accession":"S-EPMC7895412","cross_references":{"pubmed":["33556051"],"doi":["10.1371/journal.pcbi.1008681"]}}