Silicon Mechanics Supports Research Investigating Biological Pattern FormationHigh-performance cluster to aid Tufts researchers in developing new bioinformatics
Silicon Mechanics, Inc. today announced the award to Tufts University researchers of a complete high-performance computer cluster by the company and its vendor partners as part of its second annual Research Cluster Grant competition. The cluster will be a key component of a cutting-edge multidisciplinary effort to transform the way biological pattern formation is investigated. The long-term research mission is to integrate computer science, molecular biology, and biophysics to understand the processing of patterning information in living systems.
The Tufts research, conducted by an interdisciplinary group of computer scientists and biologists in collaboration with the Universidad de Sevilla, Seville, Spain, seeks to develop the world's first automated platform for the systematic discovery of emergent patterning properties from real biological data.
According to Tufts Professor of Biology Michael Levin, Ph.D., the interdisciplinary team is pursuing a new kind of bioinformatics to assist with the crucial task of integrating functional genetic data into a true systems-level understanding of the mechanisms that enable living beings to build, control, and dynamically repair their bodies.
The team's research addresses the problem of deriving predictive models of robust, large-scale patterning properties of a biological system from experimental functional data. "The ability of living beings to develop a complex organism from a single fertilized cell and of some animals to regenerate lost body-parts presents a challenge for information and complexity sciences," said Dr. Levin. "Progress in this area will have a direct impact on regenerative medicine, synthetic biology, and our fundamental understanding of evolution, as well as important implications for the engineering of highly adaptive robotics and communications networks."
The HPC cluster, valued at about $78,000, incorporates the latest technology by Silicon Mechanics and its partners NVIDIA, AMD, Kingston Technology, Mellanox, Supermicro, Seagate, and Bright Computing. Equipped with NVIDIA M2090 GPUs and AMD Opteron 6300 series processors, the HPC cluster contains a head node, eight compute nodes, two GPU nodes, and both gigabit and InfiniBand networking.
"High-performance cluster computing can make a vital contribution to interdisciplinary research in the field of developmental biology. Most important, it helps to integrate the ever-increasing volumes of high-throughput genetic and functional data to derive algorithmic models of patterning regulation," said Professor Sergei Mirkin, Ph.D., biology department chair.
Using a novel database of results on flatworm regeneration based on an original, powerful, formalized language for describing morphology and changes in pattern, the Tufts team plans to use the computer cluster to automate the discovery of complex dynamic models fitting this dataset – a task that cannot be accomplished manually. "Running the simulation environment to test morphogenetic properties of any potential model, as well as automated discovery of fitting models, requires a very high computational cost, which means the project will greatly benefit by high-performance computing," added Dr. Levin.