  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/
