Ehsan Saghapour, Joshua C Anderson, Jake Y Chen, Christopher D Willey
{"title":"KinoViz:一个用户友好的Web应用程序,用于癌症研究中的高通量基因组分析和可视化。","authors":"Ehsan Saghapour, Joshua C Anderson, Jake Y Chen, Christopher D Willey","doi":"10.21203/rs.3.rs-6431257/v1","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":519972,"journal":{"name":"Research square","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12236925/pdf/","citationCount":"0","resultStr":"{\"title\":\"KinoViz: A User-Friendly Web Application for High-Throughput Kinome Profiling Analysis and Visualization in Cancer Research.\",\"authors\":\"Ehsan Saghapour, Joshua C Anderson, Jake Y Chen, Christopher D Willey\",\"doi\":\"10.21203/rs.3.rs-6431257/v1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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.</p>\",\"PeriodicalId\":519972,\"journal\":{\"name\":\"Research square\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-06-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12236925/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Research square\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.21203/rs.3.rs-6431257/v1\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Research square","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21203/rs.3.rs-6431257/v1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
KinoViz: A User-Friendly Web Application for High-Throughput Kinome Profiling Analysis and Visualization in Cancer Research.
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.