title: Biocellion: accelerating computer simulation of multicellular biological system models.
abstract: BACKGROUND
  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.
  
  
  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.
  
  
  METHODS
  Biocellion 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.
authors: Computational Biology and Bioinformatics Group, High-performance Computing Group, Pacific Northwest National Laboratory, Richland, WA 99354, USA, Department of Computer Science, Utah State University, Logan, UT 84322, USA and Institute for Systems Biology, Seattle, WA 98109, USA.
authors: Seunghwa
authors: S
authors: Kang
authors: Computational Biology and Bioinformatics Group, High-performance Computing Group, Pacific Northwest National Laboratory, Richland, WA 99354, USA, Department of Computer Science, Utah State University, Logan, UT 84322, USA and Institute for Systems Biology, Seattle, WA 98109, USA.
authors: Simon
authors: S
authors: Kahan
authors: Computational Biology and Bioinformatics Group, High-performance Computing Group, Pacific Northwest National Laboratory, Richland, WA 99354, USA, Department of Computer Science, Utah State University, Logan, UT 84322, USA and Institute for Systems Biology, Seattle, WA 98109, USA.
authors: Jason
authors: J
authors: McDermott
authors: Computational Biology and Bioinformatics Group, High-performance Computing Group, Pacific Northwest National Laboratory, Richland, WA 99354, USA, Department of Computer Science, Utah State University, Logan, UT 84322, USA and Institute for Systems Biology, Seattle, WA 98109, USA.
authors: Nicholas
authors: N
authors: Flann
authors: Computational Biology and Bioinformatics Group, High-performance Computing Group, Pacific Northwest National Laboratory, Richland, WA 99354, USA, Department of Computer Science, Utah State University, Logan, UT 84322, USA and Institute for Systems Biology, Seattle, WA 98109, USA.
authors: Ilya
authors: I
authors: Shmulevich
mesh_terms: D000465:Algorithms; D001419:Bacteria / Q000201:enzymology; D002448:Cell Adhesion; D019295:Computational Biology; D003198:Computer Simulation; D056265:Microbial Interactions; D008954:Models, Biological; D012984:Software; D012988:Soil Microbiology; D015003:Yeasts / Q000502:physiology