Work

PhosNetVis: a web-based tool for fast kinase-substrate enrichment analysis and interactive 2D/3D network visualizations of phosphoproteomics data

Year: 2024

Type: preprint

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 in rapidly generating high-quality visualizations to gain biological insights from their phosphoproteomics datasets. It is available at: https://gumuslab.github.io/PhosNetVis/

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2402.05016

Authors: Rawal, Osho, Turhan, Berk, Peradejordi, Irene Font, Chandrasekar, Shreya, Kalayci, Selim, Gnjatic, Sacha, Johnson, Jeffrey, Bouhaddou, Mehdi, Gümüş, Zeynep H.

Institutions: Icahn School of Medicine at Mount Sinai, Sabancı Üniversitesi, Cornell University, University of California, Los Angeles

Language: English

Topic: Bioinformatics and Genomic Networks

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: green

Funders: National Institutes of Health, National Cancer Institute, National Institute of Diabetes and Digestive and Kidney Diseases

Awards: Decoding Viral Control of Host Kinase Signaling to Design Combination Therapy, Characterizing and predicting colitis in immune checkpoint blockade-treated cancer patients, PRIMAVO: Interactive exploration of cancer patient precision immune monitoring data in clinical trials, G8293452648, G9000025035, High-Dimensional Immune Monitoring of NCI-Supported Immunotherapy Trials

OpenAlex ID: W4391709211

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