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Berk Turhan 1 , Irene Font Peradejordi 2, Shreya Chandrasekar 2, Selim Kalayci 1, Jeffrey Johnson 1, Mehdi Bouhaddou 3, Zeynep H. Gümüş 1 (1 Department of Genetics and Genomics, Icahn School of Medicine at Mount Sinai, NY; 2 Cornell Tech, Cornell University, NY; 3 Institute for Quantitative and Computational Biosciences, UCLA, CA)
Protein phosphorylation is the reversible modification of a protein residue by a kinase, and is vital for cellular signaling. Different kinases can alter multiple sites on a substrate protein. Recent developments in mass spectrometry have enabled the rapid generation of massive protein phosphorylation data, as we analyze within the Human Immunology Project Consortium and the Clinical Proteomic Tumor Analysis Consortium. Despite tools to infer kinase-substrate interactions (KSIs) from these data, the lack of interactive and user-friendly tools to visualize KSI networks and phosphorylation sites is a challenge. To address this need, we present PhosNetVis, a freely available web-based tool that streamlines multiple phosphoproteomics data analysis steps within a single platform to enable easy inference, generation, and interactive exploration of KSI networks. Users can perform Kinase Enrichment Analysis (KEA) to identify significantly enriched kinases in their data and visualize the resulting networks in 3D to identify key KSIs. PhosNetVis significantly lowers the barriers to quickly translate phosphoproteomics data into biological insights and is available at phosnetvis.app.