{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/information-theoretic-analysis-of-1","title":"Information-theoretic analysis of multivariate single - cell signaling responses using SLEMI","arxiv_id":"1808.05581","date":"2018-08-16","proceeding":null,"authors":[],"abstract":"Mathematical methods of information theory constitute essential tools to\ndescribe how stimuli are encoded in activities of signaling effectors.\nExploring the information-theoretic perspective, however, remains conceptually,\nexperimentally and computationally challenging. Specifically, existing\ncomputational tools enable efficient analysis of relatively simple systems,\nusually with one input and output only. Moreover, their robust and readily\napplicable implementations are missing. Here, we propose a novel algorithm to\nanalyze signaling data within the framework of information theory. Our approach\nenables robust as well as statistically and computationally efficient analysis\nof signaling systems with high-dimensional outputs and a large number of input\nvalues. Analysis of the NF-kB single - cell signaling responses to TNF-a\nuniquely reveals that the NF-kB signaling dynamics improves discrimination of\nhigh concentrations of TNF-a with a modest impact on discrimination of low\nconcentrations. Our readily applicable R-package, SLEMI - statistical learning\nbased estimation of mutual information, allows the approach to be used by\ncomputational biologists with only elementary knowledge of information theory.","url_abs":"http://arxiv.org/abs/1808.05581v1","url_pdf":"http://arxiv.org/pdf/1808.05581v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"information-theoretic-analysis-of-1","repo_url":"https://github.com/sysbiosig/SLEMI","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1808.05581","atlas_url":"https://app.syntology.ai/?focus=1808.05581","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}