{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,6]],"date-time":"2025-08-06T12:00:30Z","timestamp":1754481630943,"version":"3.41.2"},"reference-count":44,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2023,1,23]],"date-time":"2023-01-23T00:00:00Z","timestamp":1674432000000},"content-version":"vor","delay-in-days":22,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003710","name":"Korea Health Industry Development Institute","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100003710","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,1,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Motivation<\/jats:title><jats:p>Cellular behavior is determined by complex non-linear interactions between numerous intracellular molecules that are often represented by Boolean network models. To achieve a desired cellular behavior with minimal intervention, we need to identify optimal control targets that can drive heterogeneous cellular states to the desired phenotypic cellular state with minimal node intervention. Previous attempts to realize such global stabilization were based solely on either network structure information or simple linear dynamics. Other attempts based on non-linear dynamics are not scalable.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Here, we investigate the underlying relationship between structurally identified control targets and optimal global stabilizing control targets based on non-linear dynamics. We discovered that optimal global stabilizing control targets can be identified by analyzing the dynamics between structurally identified control targets. Utilizing these findings, we developed a scalable global stabilizing control framework using both structural and dynamic information. Our framework narrows down the search space based on strongly connected components and feedback vertex sets then identifies global stabilizing control targets based on the canalization of Boolean network dynamics. We find that the proposed global stabilizing control is superior with respect to the number of control target nodes, scalability, and computational complexity.<\/jats:p><\/jats:sec><jats:sec><jats:title>Availability and implementation<\/jats:title><jats:p>We provide a GitHub repository that contains the DCGS framework written in Python as well as biological random Boolean network datasets (https:\/\/github.com\/sugyun\/DCGS).<\/jats:p><\/jats:sec><jats:sec><jats:title>Supplementary information<\/jats:title><jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p><\/jats:sec>","DOI":"10.1093\/bioinformatics\/btad045","type":"journal-article","created":{"date-parts":[[2023,1,21]],"date-time":"2023-01-21T05:14:54Z","timestamp":1674278094000},"source":"Crossref","is-referenced-by-count":6,"title":["Global stabilizing control of large-scale biomolecular regulatory networks"],"prefix":"10.1093","volume":"39","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1101-9594","authenticated-orcid":false,"given":"Sugyun","family":"An","sequence":"first","affiliation":[{"name":"Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST) , Daejeon 34141, Republic of Korea"},{"name":"Flint Research, Flint Technologies Inc , New Castle County, DE 19808, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"So-Yeong","family":"Jang","sequence":"additional","affiliation":[{"name":"Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST) , Daejeon 34141, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sang-Min","family":"Park","sequence":"additional","affiliation":[{"name":"Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST) , Daejeon 34141, Republic of Korea"},{"name":"College of Pharmacy, Chungnam National University , Daejeon 34134, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chun-Kyung","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST) , Daejeon 34141, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hoon-Min","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST) , Daejeon 34141, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7380-7142","authenticated-orcid":false,"given":"Kwang-Hyun","family":"Cho","sequence":"additional","affiliation":[{"name":"Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST) , Daejeon 34141, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2023,1,23]]},"reference":[{"key":"2023020115562183600_btad045-B1","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1103\/RevModPhys.74.47","article-title":"Statistical mechanics of complex networks","volume":"74","author":"Albert","year":"2002","journal-title":"Rev. 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