A web portal for exploring kinase-substrate interactions.

IF 3.5 2区 生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY NPJ Systems Biology and Applications Pub Date : 2024-10-03 DOI:10.1038/s41540-024-00442-5
John A P Sekar, Yan Chak Li, Avner Schlessinger, Gaurav Pandey
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引用次数: 0

Abstract

Interactions between protein kinases and their substrates are critical for the modulation of complex signaling pathways. Currently, there is a large amount of information available about kinases and their substrates in disparate public databases. However, these data are difficult to interpret in the context of cellular systems, which can be facilitated by examining interactions among multiple proteins at once, such as the network of interactions that constitute a signaling pathway. We present KiNet, a user-friendly web portal that integrates and shares information about kinase-substrate interactions from multiple databases of post-translational modifications. KiNet enables the visual exploration of these interactions in systems contexts, such as pathways, domain families, and custom protein set inputs, in an interactive fashion. We expect KiNet to be useful as a knowledge discovery tool for kinase-substrate interactions, and the aggregated KiNet dataset to be useful for protein kinase studies and systems-level analyses. The portal is available at https://kinet.kinametrix.com/ .

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探索激酶-底物相互作用的门户网站。
蛋白激酶及其底物之间的相互作用对于调节复杂的信号通路至关重要。目前,在不同的公共数据库中有大量关于激酶及其底物的信息。然而,这些数据很难在细胞系统的背景下进行解读,而同时研究多个蛋白质之间的相互作用(如构成信号通路的相互作用网络)则可以帮助我们解读这些数据。我们介绍的 KiNet 是一个用户友好型门户网站,它整合并共享多个翻译后修饰数据库中有关激酶-底物相互作用的信息。KiNet 能够以交互方式在系统上下文(如通路、结构域家族和自定义蛋白质集输入)中对这些相互作用进行可视化探索。我们希望 KiNet 能够成为激酶-底物相互作用的知识发现工具,而汇总的 KiNet 数据集将有助于蛋白激酶研究和系统级分析。门户网站:https://kinet.kinametrix.com/ 。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
NPJ Systems Biology and Applications
NPJ Systems Biology and Applications Mathematics-Applied Mathematics
CiteScore
5.80
自引率
0.00%
发文量
46
审稿时长
8 weeks
期刊介绍: npj Systems Biology and Applications is an online Open Access journal dedicated to publishing the premier research that takes a systems-oriented approach. The journal aims to provide a forum for the presentation of articles that help define this nascent field, as well as those that apply the advances to wider fields. We encourage studies that integrate, or aid the integration of, data, analyses and insight from molecules to organisms and broader systems. Important areas of interest include not only fundamental biological systems and drug discovery, but also applications to health, medical practice and implementation, big data, biotechnology, food science, human behaviour, broader biological systems and industrial applications of systems biology. We encourage all approaches, including network biology, application of control theory to biological systems, computational modelling and analysis, comprehensive and/or high-content measurements, theoretical, analytical and computational studies of system-level properties of biological systems and computational/software/data platforms enabling such studies.
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