{"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/methods-for-characterizing-the-epigenetic","title":"Methods for Characterizing the Epigenetic Attractors Landscape Associated with Boolean Gene Regulatory Networks","arxiv_id":"1510.04230","date":"2015-10-14","proceeding":null,"authors":[],"abstract":"Gene regulatory network (GRN) modeling is a well-established theoretical\nframework for the study of cell-fate specification during developmental\nprocesses. Recently, dynamical models of GRNs have been taken as a basis for\nformalizing the metaphorical model of Waddington's epigenetic landscape,\nproviding a natural extension for the general protocol of GRN modeling. In this\ncontribution we present in a coherent framework a novel implementation of two\npreviously proposed general frameworks for modeling the Epigenetic Attractors\nLandscape associated with boolean GRNs: the inter-attractor and inter-state\ntransition approaches. We implement novel algorithms for estimating\ninter-attractor transition probabilities without necessarily depending on\nintensive single-event simulations. We analyze the performance and sensibility\nto parameter choices of the algorithms for estimating inter-attractor\ntransition probabilities using three real GRN models. Additionally, we present\na side-by-side analysis of downstream analysis tools such as the attractors'\ntemporal and global ordering in the EAL. Overall, we show how the methods\ncomplement each other using a real case study: a cellular-level GRN model for\nepithelial carcinogenesis. We expect the toolkit and comparative analyses put\nforward here to be a valuable additional re- source for the systems biology\ncommunity interested in modeling cellular differentiation and reprogramming\nboth in normal and pathological developmental processes.","url_abs":"http://arxiv.org/abs/1510.04230v1","url_pdf":"http://arxiv.org/pdf/1510.04230v1.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":"methods-for-characterizing-the-epigenetic","repo_url":"https://github.com/JoseDDesoj/Epigenetic-Attractors-Landscape-R","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}