KINAID: an orthology-based kinase-substrate prediction and analysis tool for phosphoproteomics.

Javed M Aman, Audrey W Zhu, Martin Wühr, Stanislav Y Shvartsman, Mona Singh
{"title":"KINAID: an orthology-based kinase-substrate prediction and analysis tool for phosphoproteomics.","authors":"Javed M Aman, Audrey W Zhu, Martin Wühr, Stanislav Y Shvartsman, Mona Singh","doi":"10.1093/bioinformatics/btaf300","DOIUrl":null,"url":null,"abstract":"<p><strong>Summary: </strong>Proteome-wide datasets of phosphorylated peptides, either measured in a condition of interest or in response to perturbations, are increasingly becoming available for model organisms across the evolutionary spectrum. We introduce KINAID (KINase Activity and Inference Dashboard), an interactive and extensible tool written in Dash/Plotly, that predicts kinase-substrate interactions, uncovers and displays kinases whose substrates are enriched amongst phosphorylated peptides, interactively illustrates kinase-substrate interactions, and clusters phosphopeptides targeted by similar kinases. KINAID is the first tool of its kind that can analyze data from not only Homo sapiens but also 10 additional model organisms (including Mus musculus, Danio rerio, Drosophila melanogaster, Caenorhabditis elegans, and Saccharomyces cerevisiae). We demonstrate KINAID's utility by applying it to recently published S. cerevisiae phosphoproteomics data.</p><p><strong>Availability and implementation: </strong>Webserver is available at https://kinaid.princeton.edu; open-source python library is available at https://github.com/Singh-Lab/kinaid; archive is available at https://doi.org/10.24433/CO.8460107.v1.</p>","PeriodicalId":93899,"journal":{"name":"Bioinformatics (Oxford, England)","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bioinformatics (Oxford, England)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/bioinformatics/btaf300","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Summary: Proteome-wide datasets of phosphorylated peptides, either measured in a condition of interest or in response to perturbations, are increasingly becoming available for model organisms across the evolutionary spectrum. We introduce KINAID (KINase Activity and Inference Dashboard), an interactive and extensible tool written in Dash/Plotly, that predicts kinase-substrate interactions, uncovers and displays kinases whose substrates are enriched amongst phosphorylated peptides, interactively illustrates kinase-substrate interactions, and clusters phosphopeptides targeted by similar kinases. KINAID is the first tool of its kind that can analyze data from not only Homo sapiens but also 10 additional model organisms (including Mus musculus, Danio rerio, Drosophila melanogaster, Caenorhabditis elegans, and Saccharomyces cerevisiae). We demonstrate KINAID's utility by applying it to recently published S. cerevisiae phosphoproteomics data.

Availability and implementation: Webserver is available at https://kinaid.princeton.edu; open-source python library is available at https://github.com/Singh-Lab/kinaid; archive is available at https://doi.org/10.24433/CO.8460107.v1.

KINAID:基于同源的磷酸化蛋白质组学激酶底物预测和分析工具。
摘要:磷酸化肽的蛋白质组范围数据集,无论是在感兴趣的条件下测量还是在对扰动的响应中测量,越来越多地用于整个进化谱中的模式生物。我们介绍了KINAID(激酶活性和推断仪表盘),这是一个用Dash/Plotly编写的交互式和可扩展的工具,可以预测激酶与底物的相互作用,揭示和显示底物在磷酸化肽中富集的激酶,交互说明激酶与底物的相互作用,并将类似激酶靶向的磷酸肽聚集在一起。KINAID是同类工具中第一个不仅可以分析智人的数据,还可以分析另外10种模式生物(包括M. musus、D. rerio、D. melanogaster、C. elegans和S. cerevisiae)的数据。我们通过将KINAID应用于最近发表的酿酒葡萄球菌磷蛋白组学数据来证明其实用性。可用性和实现:web服务器在https://kinaid.princeton.edu;开源python库:https://github.com/Singh-Lab/kinaid;信息:可在Bioinformatics在线获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信