{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T10:01:16Z","timestamp":1777716076630,"version":"3.51.4"},"reference-count":45,"publisher":"SAGE Publications","issue":"2-3","license":[{"start":{"date-parts":[[2005,2,1]],"date-time":"2005-02-01T00:00:00Z","timestamp":1107216000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["The International Journal of Robotics Research"],"published-print":{"date-parts":[[2005,2]]},"abstract":"<jats:p>\n                    <jats:italic toggle=\"yes\">In this paper we propose modeling and analysis techniques for genetic networks                     that provide biologists with insight into the dynamics of such systems. Central                     to our modeling approach is the framework of hybrid systems and our analysis                     tools are derived from formal analysis of such systems. Given a set of states                     characterizing a property of biological interest P<\/jats:italic>\n                    <jats:italic toggle=\"yes\">, we present the Multi-Affine Rectangular Partition (MARP) algorithm for the                     construction of a set of infeasible states I that will never reach P and the                     Rapidly Exploring Random Forest of Trees (RRFT) algorithm for the construction                     of a set of feasible states F that will reach P<\/jats:italic>\n                    .\n                    <jats:italic toggle=\"yes\">These techniques are                     scalable to high dimensions and can incorporate uncertainty (partial knowledge                     of kinetic parameters and state uncertainty).We apply these methods to                     understand the genetic interactions involved in the phenomenon of luminescence                     production in the marine bacterium<\/jats:italic>\n                    V. fischeri.\n                  <\/jats:p>","DOI":"10.1177\/0278364905050359","type":"journal-article","created":{"date-parts":[[2005,1,26]],"date-time":"2005-01-26T07:27:56Z","timestamp":1106724476000},"page":"219-235","source":"Crossref","is-referenced-by-count":13,"title":["Computational Techniques for Analysis of Genetic Network Dynamics"],"prefix":"10.1177","volume":"24","author":[{"given":"Calin","family":"Belta","sequence":"first","affiliation":[{"name":"Drexel University, Philadelphia, PA, USA,"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Joel M.","family":"Esposito","sequence":"additional","affiliation":[{"name":"US Naval Academy, Annapolis, MD, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jongwoo","family":"Kim","sequence":"additional","affiliation":[{"name":"University of Pennsylvania, Philadelphia, PA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vijay","family":"Kumar","sequence":"additional","affiliation":[{"name":"University of Pennsylvania, Philadelphia, PA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2005,2]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"crossref","unstructured":"Alur R. 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