{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T13:08:23Z","timestamp":1753880903227,"version":"3.41.2"},"reference-count":33,"publisher":"World Scientific Pub Co Pte Ltd","issue":"05","funder":[{"DOI":"10.13039\/501100005375","name":"Latvian Council of Science Project","doi-asserted-by":"publisher","award":["lzp-2019\/1-0432"],"award-info":[{"award-number":["lzp-2019\/1-0432"]}],"id":[{"id":"10.13039\/501100005375","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Bioinform. Comput. Biol."],"published-print":{"date-parts":[[2022,10]]},"abstract":"<jats:p> We present hybrid system-based gene regulatory network models for lambda, HK022, and Mu bacteriophages together with dynamics analysis of the modeled networks. The proposed lambda phage model LPH2 is based on an earlier work and incorporates more recent biological assumptions about the underlying gene regulatory mechanism, HK022, and Mu phage models are new. All three models provide accurate representations of experimentally observed lytic and lysogenic behavioral cycles. Importantly, the models also imply that lysis and lysogeny are the only stable behaviors that can occur in the modeled networks. In addition, the models allow to derive switching conditions that irrevocably lead to either lytic or lysogenic behavioral cycle as well as constraints that are required for their biological feasibility. For LPH2 model the feasibility constraints place two mutually independent requirements on comparative order of cro and cI protein binding site affinities. However, HK022 model, while broadly similar, does not require any of these constraints. Biologically very different lysis\u2013lysogeny switching mechanism of Mu phage is also accurately reproduced by its model. In general the results show that hybrid system model (HSM) hybrid system framework can be successfully applied to modeling small ([Formula: see text] gene) regulatory networks and used for comprehensive analysis of model dynamics and stable behavior regions. <\/jats:p>","DOI":"10.1142\/s0219720022500214","type":"journal-article","created":{"date-parts":[[2022,8,31]],"date-time":"2022-08-31T14:45:11Z","timestamp":1661957111000},"source":"Crossref","is-referenced-by-count":1,"title":["Behavioral dynamics of bacteriophage gene regulatory networks"],"prefix":"10.1142","volume":"20","author":[{"given":"Gatis","family":"Melkus","sequence":"first","affiliation":[{"name":"Institute of Mathematics and Computer Science, University of Latvia, Rainis Boulevard 29, Riga LV-1459, Latvia"}]},{"given":"Karlis","family":"Cerans","sequence":"additional","affiliation":[{"name":"Institute of Mathematics and Computer Science, University of Latvia, Rainis Boulevard 29, Riga LV-1459, Latvia"}]},{"given":"Karlis","family":"Freivalds","sequence":"additional","affiliation":[{"name":"Institute of Mathematics and Computer Science, University of Latvia, Rainis Boulevard 29, Riga LV-1459, Latvia"}]},{"given":"Lelde","family":"Lace","sequence":"additional","affiliation":[{"name":"Institute of Mathematics and Computer Science, University of Latvia, Rainis Boulevard 29, Riga LV-1459, Latvia"}]},{"given":"Darta","family":"Zajakina","sequence":"additional","affiliation":[{"name":"Institute of Mathematics and Computer Science, University of Latvia, Rainis Boulevard 29, Riga LV-1459, Latvia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2283-2978","authenticated-orcid":false,"given":"Juris","family":"Viksna","sequence":"additional","affiliation":[{"name":"Institute of Mathematics and Computer Science, University of Latvia, Rainis Boulevard 29, Riga LV-1459, 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