High Performance Computing for Multiscale Modeling of Biological Systems

一、总体-摘要

I. Overall - Abstract We propose to renew the Biomedical Technology and Research Resource (BTRR) on High Performance Computing for Multiscale Modeling of Biological Systems, hereafter referred to as MMBioS. MMBioS is a joint effort between the University of Pittsburgh (Pitt; lead institution), Carnegie Mellon University (CMU), the Pittsburgh Supercomputing Center (PSC), and the Salk Institute for Biological Studies (Salk). Our mission is to continue to develop computational methods and usable software tools to advance research and training at the interface between computing technology and life sciences. Our biological theme remains: realistic and efficient modeling, analysis and simulations of molecular and cellular structure and dynamics toward understanding and predicting the origin and mechanism of biological function/dysfunction at multiple scales, with focus on synaptic signaling and regulation events, thus facilitating the discovery of new treatments against nervous and immune systems' disorders. Building on the progress made during the past award in starting to fill the gap between modeling efforts at disparate scales of structural biology, cellular microphysiology and large- scale bioimage analysis, we now further expand our efforts toward developing more powerful tools and an integrated platform for efficient implementation and use of our technology. We have increased the scope and number of our Technology Research and Development Projects from 3 to 4, to advance and enable the adaptation of molecular modeling (TR&D1), cell modeling (TR&D2), (cellular) network modeling (TR&D3), and image-derived modeling (TR&D4) methods and software to new challenges. These are driven by seven Driving Biomedical Projects (DBPs) on: the dynamics of neurotransmitter transporters at both molecular and cellular levels (DBP1; NIH and U of Florida); regulation and binding to PSD-95 and its relation to AMPAR trafficking (DBP2; Caltech), multiscale modeling of dopamine transporter function (DBP3; Pitt); spatiotemporal modeling of T cell signaling (DBP4; Bristol, UK); constructing a dynamic, spatial map of transcription and chromatin structure (DBP6; NIH); structure and function of synapses (DBP7; UT Austin); and scalable approaches to modeling using large sets of rules and images (DBP8; Harvard). Previous DBP5 (Allen Brain Institute) on functional connectomics has been successfully completed. We will continue our vigorous training and dissemination programs, and a broad range of Collaboration of Service Projects (C&SPs), taking advantage of the unique experience and capabilities of the PSC, the strengths of the Departments of Computational and Systems Biology (Pitt) and Computational Biology (CMU), and cutting-edge research at the Computational Neurobiology Laboratory at Salk.