Rawal, Osho and Turhan, Berk and Peradejordi, Irene Font and Chandrasekar, Shreya and Kalayci, Selim and Gnjatic, Sacha and Johnson, Jeffrey and Bouhaddou, Mehdi and Gümüş, Zeynep H. (2025) PhosNetVis: a web-based tool for fast kinase-substrate enrichment analysis and interactive 2D/3D network visualizations of phosphoproteomics data. Patterns, 6 (1). ISSN 2666-3899
Full text not available from this repository. (Request a copy)
Official URL: https://dx.doi.org/10.1016/j.patter.2024.101148
Abstract
Protein phosphorylation involves the reversible modification of a protein (substrate) residue by another protein (kinase). Liquid chromatography-mass spectrometry studies are rapidly generating massive protein phosphorylation datasets across multiple conditions. Researchers then must infer kinases responsible for changes in phosphosites of each substrate. However, tools that infer kinase-substrate interactions (KSIs) are not optimized to interactively explore the resulting large and complex networks, significant phosphosites, and states. There is thus an unmet need for a tool that facilitates user-friendly analysis, interactive exploration, visualization, and communication of phosphoproteomics datasets. We present PhosNetVis, a web-based tool for researchers of all computational skill levels to easily infer, generate, and interactively explore KSI networks in 2D or 3D by streamlining phosphoproteomics data analysis steps within a single tool. PhostNetVis lowers barriers for researchers by rapidly generating high-quality visualizations to gain biological insights from their phosphoproteomics datasets. It is available at https://gumuslab.github.io/PhosNetVis/.
Item Type: | Article |
---|---|
Uncontrolled Keywords: | 3D visualization; CPTAC; fast kinase-substrate enrichment analysis; interactive visualization; kinase-substrate interaction; network visualization; phosphoproteomics; phosphorylation |
Divisions: | Faculty of Engineering and Natural Sciences |
Depositing User: | Berk Turhan |
Date Deposited: | 27 Mar 2025 10:19 |
Last Modified: | 27 Mar 2025 10:19 |
URI: | https://research.sabanciuniv.edu/id/eprint/51292 |