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KinoViz: A User-Friendly Web Application for High-Throughput Kinome Profiling Analysis and Visualization in Cancer
Ehsan Saghapour1, Joshua C Anderson1, Jake Y Chen1
1The University of Alabama at Birmingham.
Abstract:
Kinases, at the signaling level, dynamically mediate uncontrolled cellular growth, survival and other cancer supporting processes. This, paired with the inherent druggability of kinases, points to the importance of measuring kinase activity, and that of inhibitors against them, directly, and to analyze this accurately. High-throughput kinome profiling technologies, such as the PamStation®12, allow researchers to kinetically capture kinase activity, against a multitude of peptide targets simultaneously. Yet, the complex datasets produced often require advanced computational tools and bioinformatics expertise to properly analyze that are not intuitive or readily available. To address this gap, we developed KinoViz, a web-based application to simplify analysis and visualization of kinome array data. KinoViz offers a suite of interactive tools that enables users to upload raw peptide phosphorylation datasets and conduct in-depth analyses without the need for coding knowledge. Key features include modules for visualizing kinetic phosphorylation curves, identifying statistically significant peptide changes, exploring individual peptide profiles, and generating insightful visualizations such as heatmaps, network diagrams, and dimensionality reduction plots (PCA, UMAP). By making complex kinomic data more accessible and interpretable, KinoViz allows researchers to rapidly generate interactive visualizations and comparative analyses. We aim to expand KinoViz's analytical capabilities for more advanced use, including use in direct translational drug discovery.
Insights
KinoViz simplifies the analysis of complex kinome profiling data. This web application provides interactive tools for researchers to visualize and interpret kinase activity, accelerating drug discovery.
Area of Science:
- Biochemistry
- Bioinformatics
- Computational Biology
Background:
- Kinases are crucial signaling proteins regulating cellular processes, making them key targets in cancer.
- Measuring kinase activity and inhibitor efficacy is vital for cancer research and drug development.
- Existing high-throughput kinome profiling generates complex data requiring specialized bioinformatics expertise.
Purpose of the Study:
- To develop an accessible web-based application, KinoViz, for the analysis and visualization of kinome array data.
- To bridge the gap between complex kinomic datasets and researchers lacking advanced computational skills.
- To enable rapid interpretation of kinase activity and comparative analyses.
Main Methods:
- Development of KinoViz, a user-friendly, web-based application.
- Implementation of interactive modules for data upload and analysis of peptide phosphorylation datasets.
- Integration of visualization tools including kinetic curves, heatmaps, network diagrams, and dimensionality reduction plots (PCA, UMAP).
Main Results:
- KinoViz enables users to upload raw data and perform in-depth analyses without coding.
- The application facilitates visualization of kinetic phosphorylation, identification of significant changes, and exploration of peptide profiles.
- Researchers can rapidly generate interactive visualizations and comparative analyses of kinomic data.
Conclusions:
- KinoViz significantly enhances the accessibility and interpretability of complex kinome array data.
- The tool empowers researchers to conduct sophisticated analyses, aiding in understanding kinase signaling pathways.
- Future expansion aims to support advanced applications, including translational drug discovery.
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