Streaming interaction mapping of extreme post‑translational modification interaction structures

Streaming interaction mapping of extreme post‑translational modification interaction structures | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Method Article Streaming interaction mapping of extreme post‑translational modification interaction structures Kim Dae Hoon This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9646879/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract High-dimensional interaction mapping in proteomics and multi-omics often relies on dense N×N similarity matrices, which quickly become impractical as feature counts grow. Here, we present Local Information Criticality Principle with Interaction-Structure Top-K Preservation (LICP-ISTP), a deterministic, matrix-free streaming framework that computes a band-limited interaction kernel and records (i) block-level mean interaction structure, (ii) the distribution of interaction magnitudes, and (iii) the exact Top-K extreme interaction pairs, all in a single pass without constructing a dense pairwise matrix. Using public CPTAC colon adenocarcinoma phosphoproteomics data, we observed heavy-tailed interaction-magnitude behavior and structured extreme-interaction offsets under identical computational settings for tumor and adjacent normal tissue. Bioinformatics proteomics phosphoproteomics post-translational modification multi-omics interaction mapping matrix-free computation streaming algorithm CPTAC colon adenocarcinoma tumor-normal comparison extreme interaction pairs LICP-ISTP Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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