This subproject is one of many research subprojects utilizing theresources provided by a Center grant funded by NIH/NCRR. The subproject andinvestigator (PI) may have received primary funding from another NIH source,and thus could be represented in other CRISP entries. The institution listed isfor the Center, which is not necessarily the institution for the investigator.
The aim of the BioSimGrid project is to make the results of large-scale computer simulations of biomolecules more accessible to the biological community. Such simulations of the motions of proteins are a key component in understanding how the structure of a protein is related to its dynamic function.A major impediment to making such simulations available to biologists has been the absence of a database of simulation results. Using the power of the Grid the developers hope to solve these problems, thus enabling them to take a comparative, i.e. genuinely biological, approach to analysis of simulation data.In an ideal world, all simulation data would be available to all interested parties. However, at present simulation data reside in the home laboratory and are not accessible to other research groups. One solution to this problem would be to deposit all simulation results in a centralised database, but in reality the vast quantities of data mean that rapid access would become impossible. The Grid provides the opportunity to draw together distributed collections of simulation data in disparate formats, whilst maintaining a centrally accessible federated database.
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|Morgan, Ashley E; Wozniak, Curtis J; Gulati, Sarthak et al. (2017) Association of Uneven MitraClip Application and Leaflet Stress in a Finite Element Model. JAMA Surg 152:111-114|
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|Bucero, Marta Abril; Bajaj, Chandrajit; Mourrain, Bernard (2016) On the construction of general cubature formula by flat extensions. Linear Algebra Appl 502:104-125|
|Ebeida, Mohamed S; Rushdi, Ahmad A; Awad, Muhammad A et al. (2016) Disk Density Tuning of a Maximal Random Packing. Comput Graph Forum 35:259-269|
|Yang, Pei-Chi; Boras, Britton W; Jeng, Mao-Tsuen et al. (2016) A Computational Modeling and Simulation Approach to Investigate Mechanisms of Subcellular cAMP Compartmentation. PLoS Comput Biol 12:e1005005|
|Watson, Shana R; Liu, Piaomu; Peña, Edsel A et al. (2016) Comparison of Aortic Collagen Fiber Angle Distribution in Mouse Models of Atherosclerosis Using Second-Harmonic Generation (SHG) Microscopy. Microsc Microanal 22:55-62|
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