{"user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","title":"Evolution of bow-tie architectures in biology","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)","image":"/images/cc_by.png"},"publist_id":"5278","article_processing_charge":"No","file":[{"content_type":"application/pdf","checksum":"b8aa66f450ff8de393014b87ec7d2efb","access_level":"open_access","file_name":"IST-2016-452-v1+1_journal.pcbi.1004055.pdf","relation":"main_file","file_size":1811647,"date_created":"2018-12-12T10:15:39Z","date_updated":"2020-07-14T12:45:17Z","file_id":"5161","creator":"system"}],"day":"23","year":"2015","ddc":["576"],"citation":{"short":"T. Friedlander, A. Mayo, T. Tlusty, U. Alon, PLoS Computational Biology 11 (2015).","mla":"Friedlander, Tamar, et al. “Evolution of Bow-Tie Architectures in Biology.” PLoS Computational Biology, vol. 11, no. 3, Public Library of Science, 2015, doi:10.1371/journal.pcbi.1004055.","chicago":"Friedlander, Tamar, Avraham Mayo, Tsvi Tlusty, and Uri Alon. “Evolution of Bow-Tie Architectures in Biology.” PLoS Computational Biology. Public Library of Science, 2015. https://doi.org/10.1371/journal.pcbi.1004055.","ista":"Friedlander T, Mayo A, Tlusty T, Alon U. 2015. Evolution of bow-tie architectures in biology. PLoS Computational Biology. 11(3).","ama":"Friedlander T, Mayo A, Tlusty T, Alon U. Evolution of bow-tie architectures in biology. PLoS Computational Biology. 2015;11(3). doi:10.1371/journal.pcbi.1004055","apa":"Friedlander, T., Mayo, A., Tlusty, T., & Alon, U. (2015). Evolution of bow-tie architectures in biology. PLoS Computational Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1004055","ieee":"T. Friedlander, A. Mayo, T. Tlusty, and U. Alon, “Evolution of bow-tie architectures in biology,” PLoS Computational Biology, vol. 11, no. 3. Public Library of Science, 2015."},"date_published":"2015-03-23T00:00:00Z","publisher":"Public Library of Science","author":[{"last_name":"Friedlander","first_name":"Tamar","id":"36A5845C-F248-11E8-B48F-1D18A9856A87","full_name":"Friedlander, Tamar"},{"last_name":"Mayo","full_name":"Mayo, Avraham","first_name":"Avraham"},{"first_name":"Tsvi","full_name":"Tlusty, Tsvi","last_name":"Tlusty"},{"full_name":"Alon, Uri","first_name":"Uri","last_name":"Alon"}],"related_material":{"record":[{"relation":"research_data","status":"public","id":"9718"},{"status":"public","relation":"research_data","id":"9773"}]},"_id":"1827","ec_funded":1,"doi":"10.1371/journal.pcbi.1004055","month":"03","status":"public","intvolume":" 11","abstract":[{"lang":"eng","text":"Bow-tie or hourglass structure is a common architectural feature found in many biological systems. A bow-tie in a multi-layered structure occurs when intermediate layers have much fewer components than the input and output layers. Examples include metabolism where a handful of building blocks mediate between multiple input nutrients and multiple output biomass components, and signaling networks where information from numerous receptor types passes through a small set of signaling pathways to regulate multiple output genes. Little is known, however, about how bow-tie architectures evolve. Here, we address the evolution of bow-tie architectures using simulations of multi-layered systems evolving to fulfill a given input-output goal. We find that bow-ties spontaneously evolve when the information in the evolutionary goal can be compressed. Mathematically speaking, bow-ties evolve when the rank of the input-output matrix describing the evolutionary goal is deficient. The maximal compression possible (the rank of the goal) determines the size of the narrowest part of the network—that is the bow-tie. A further requirement is that a process is active to reduce the number of links in the network, such as product-rule mutations, otherwise a non-bow-tie solution is found in the evolutionary simulations. This offers a mechanism to understand a common architectural principle of biological systems, and a way to quantitate the effective rank of the goals under which they evolved."}],"oa":1,"quality_controlled":"1","has_accepted_license":"1","publication_status":"published","file_date_updated":"2020-07-14T12:45:17Z","oa_version":"Published Version","isi":1,"scopus_import":"1","issue":"3","project":[{"_id":"25681D80-B435-11E9-9278-68D0E5697425","grant_number":"291734","name":"International IST Postdoc Fellowship Programme","call_identifier":"FP7"}],"type":"journal_article","language":[{"iso":"eng"}],"pubrep_id":"452","volume":11,"department":[{"_id":"GaTk"}],"publication":"PLoS Computational Biology","date_updated":"2025-09-23T08:43:16Z","external_id":{"isi":["000352195700006"]},"date_created":"2018-12-11T11:54:14Z"}