{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T11:36:22Z","timestamp":1777462582041,"version":"3.51.4"},"reference-count":37,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2018,6,28]],"date-time":"2018-06-28T00:00:00Z","timestamp":1530144000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"name":"Open Competitive Grand Challenge Seed"},{"DOI":"10.13039\/501100007488","name":"Indian Institute of Technology","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100007488","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Kharagpur"},{"name":"Inspire Fellowship","award":["IF150632"],"award-info":[{"award-number":["IF150632"]}]},{"DOI":"10.13039\/501100006143","name":"Department of Science and Technology","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100006143","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Government of India"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,1,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>In Computational Cell Biology, whole-cell modeling and simulation is an absolute requirement to analyze and explore the cell of an organism. Despite few individual efforts on modeling, the prime obstacle hindering its development and progress is its compute-intensive nature. Towards this end, little knowledge is available on how to reduce the enormous computational overhead and which computational systems will be of use.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>In this article, we present a network-based zoning approach that could potentially be utilized in the parallelization of whole-cell simulations. Firstly, we construct the protein\u2013protein interaction graph of the whole-cell of an organism using experimental data from various sources. Based on protein interaction information, we predict protein locality and allocate confidence score to the interactions accordingly. We then identify the modules of strictly localized interacting proteins by performing interaction graph clustering based on the confidence score of the interactions. By applying this method to Escherichia coli K12, we identified 188 spatially localized clusters. After a thorough Gene Ontology-based analysis, we proved that the clusters are also in functional proximity. We then conducted Principal Coordinates Analysis to predict the spatial distribution of the clusters in the simulation space. Our automated computational techniques can partition the entire simulation space (cell) into simulation sub-cells. Each of these sub-cells can be simulated on separate computing units of the High-Performance Computing (HPC) systems. We benchmarked our method using proteins. However, our method can be extended easily to add other cellular components like DNA, RNA and metabolites.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>\u2003<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Supplementary information<\/jats:title>\n                  <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/bty530","type":"journal-article","created":{"date-parts":[[2018,6,27]],"date-time":"2018-06-27T19:37:29Z","timestamp":1530128249000},"page":"88-94","source":"Crossref","is-referenced-by-count":7,"title":["A network-based zoning for parallel whole-cell simulation"],"prefix":"10.1093","volume":"35","author":[{"given":"Barnali","family":"Das","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, Indian Institute of Technology Kharagpur, West Bengal, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Abhijeet Rajendra","family":"Patil","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Indian Institute of Technology Kharagpur, West Bengal, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4119-3788","authenticated-orcid":false,"given":"Pralay","family":"Mitra","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Indian Institute of Technology Kharagpur, West Bengal, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2018,6,28]]},"reference":[{"key":"2023013107205946600_bty530-B1","first-page":"1","volume-title":"Encyclopedia of Measurement and Statistics","author":"Abdi","year":"2007"},{"key":"2023013107205946600_bty530-B2","doi-asserted-by":"crossref","first-page":"345","DOI":"10.1145\/116873.116880","article-title":"Voronoi diagrams\u2014a survey of a fundamental geometric data structure","volume":"23","author":"Aurenhammer","year":"1991","journal-title":"ACM Comput. 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