{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T23:29:25Z","timestamp":1768346965065,"version":"3.49.0"},"reference-count":38,"publisher":"Oxford University Press (OUP)","issue":"21","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2014,11,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: Biological system behaviors are often the outcome of complex interactions among a large number of cells and their biotic and abiotic environment. Computational biologists attempt to understand, predict and manipulate biological system behavior through mathematical modeling and computer simulation. Discrete agent-based modeling (in combination with high-resolution grids to model the extracellular environment) is a popular approach for building biological system models. However, the computational complexity of this approach forces computational biologists to resort to coarser resolution approaches to simulate large biological systems. High-performance parallel computers have the potential to address the computing challenge, but writing efficient software for parallel computers is difficult and time-consuming.<\/jats:p>\n               <jats:p>Results: We have developed Biocellion , a high-performance software framework, to solve this computing challenge using parallel computers. To support a wide range of multicellular biological system models, Biocellion asks users to provide their model specifics by filling the function body of pre-defined model routines. Using Biocellion , modelers without parallel computing expertise can efficiently exploit parallel computers with less effort than writing sequential programs from scratch. We simulate cell sorting, microbial patterning and a bacterial system in soil aggregate as case studies.<\/jats:p>\n               <jats:p>Availability and implementation: \u00a0Biocellion runs on x86 compatible systems with the 64 bit Linux operating system and is freely available for academic use. Visit http:\/\/biocellion.com for additional information.<\/jats:p>\n               <jats:p>Contact: \u00a0seunghwa.kang@pnnl.gov<\/jats:p>","DOI":"10.1093\/bioinformatics\/btu498","type":"journal-article","created":{"date-parts":[[2014,7,27]],"date-time":"2014-07-27T00:29:24Z","timestamp":1406420964000},"page":"3101-3108","source":"Crossref","is-referenced-by-count":97,"title":["<i>Biocellion<\/i>\n            : accelerating computer simulation of multicellular biological system models"],"prefix":"10.1093","volume":"30","author":[{"given":"Seunghwa","family":"Kang","sequence":"first","affiliation":[{"name":"1 Computational Biology and Bioinformatics Group, 2 High-performance Computing Group, Pacific Northwest National Laboratory, Richland, WA 99354, USA, 3 Department of Computer Science, Utah State University, Logan, UT 84322, USA and 4 Institute for Systems Biology, Seattle, WA 98109, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Simon","family":"Kahan","sequence":"additional","affiliation":[{"name":"1 Computational Biology and Bioinformatics Group, 2 High-performance Computing Group, Pacific Northwest National Laboratory, Richland, WA 99354, USA, 3 Department of Computer Science, Utah State University, Logan, UT 84322, USA and 4 Institute for Systems Biology, Seattle, WA 98109, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jason","family":"McDermott","sequence":"additional","affiliation":[{"name":"1 Computational Biology and Bioinformatics Group, 2 High-performance Computing Group, Pacific Northwest National Laboratory, Richland, WA 99354, USA, 3 Department of Computer Science, Utah State University, Logan, UT 84322, USA and 4 Institute for Systems Biology, Seattle, WA 98109, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nicholas","family":"Flann","sequence":"additional","affiliation":[{"name":"1 Computational Biology and Bioinformatics Group, 2 High-performance Computing Group, Pacific Northwest National Laboratory, Richland, WA 99354, USA, 3 Department of Computer Science, Utah State University, Logan, UT 84322, USA and 4 Institute for Systems Biology, Seattle, WA 98109, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ilya","family":"Shmulevich","sequence":"additional","affiliation":[{"name":"1 Computational Biology and Bioinformatics Group, 2 High-performance Computing Group, Pacific Northwest National Laboratory, Richland, WA 99354, USA, 3 Department of Computer Science, Utah State University, Logan, UT 84322, USA and 4 Institute for Systems Biology, Seattle, WA 98109, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2014,7,26]]},"reference":[{"key":"2023012711573485600_btu498-B1","doi-asserted-by":"crossref","first-page":"857","DOI":"10.1006\/bulm.1998.0042","article-title":"Continuous and discrete mathematical models of tumor-induced angiogenesis","volume":"60","author":"Anderson","year":"1998","journal-title":"Bull. 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