{"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/enhancing-boolean-networks-with-continuous","title":"Enhancing Boolean networks with continuous logical operators and edge tuning","arxiv_id":"1407.1135","date":"2019-03-20","proceeding":null,"authors":[],"abstract":"Due to the scarcity of quantitative details about biological phenomena,\nquantitative modeling in systems biology can be compromised, especially at the\nsubcellular scale. One way to get around this is qualitative modeling because\nit requires few to no quantitative information. One of the most popular\nqualitative modeling approaches is the Boolean network formalism. However,\nBoolean models allow variables to take only two values, which can be too\nsimplistic in some cases. The present work proposes a modeling approach derived\nfrom Boolean networks where continuous logical operators are used and where\nedges can be tuned. Using continuous logical operators allows variables to be\nmore finely valued while remaining qualitative. To consider that some\nbiological interactions can be slower or weaker than other ones, edge states\nare also computed in order to modulate in speed and strength the signal they\nconvey. The proposed formalism is illustrated on a toy network coming from the\nepidermal growth factor receptor signaling pathway. The obtained simulations\nshow that continuous results are produced, thus allowing finer analysis. The\nsimulations also show that modulating the signal conveyed by the edges allows\nto incorporate knowledge about the interactions they model. The goal is to\nprovide enhancements in the ability of qualitative models to simulate the\ndynamics of biological networks while limiting the need of quantitative\ninformation.","url_abs":"http://arxiv.org/abs/1407.1135v6","url_pdf":"http://arxiv.org/pdf/1407.1135v6.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":"enhancing-boolean-networks-with-continuous","repo_url":"https://github.com/arnaudporet/smoosim","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}