High performance computing for computational Biology

计算生物学的高性能计算

• 批准号: 375062-2009
• 负责人: Lilien, Ryan
• 金额: $ 5.9万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Research Tools and Instruments - Category 1 (<$150,000)
• 财政年份: 2008
• 资助国家: 加拿大
• 起止时间: 2008-01-01 至 2009-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=412072
• 关键词: performance; computing; computational; Biology

Research in our Computational Biology group centers around the development and application of efficient computational techniques to solve data analysis and modeling problems in the biomedical sciences (organic chemistry, biochemistry, and biology). Our lab aims to produce algorithms that are provably correct under a biologically reasonable set of criteria and that are robust to experimental noise and missing data. We study organic molecules from DNA (the molecular blueprint of life), to small ligands (pharmaceutically interesting molecules with tens of atoms), to large proteins (enormous molecules with thousands of atoms). We are interested in characterizing the structure and function of these molecules and then utilizing this information to assist our biological collaborators in the development of new pharmaceuticals and models of disease. In Computer Science, problems are generally sanitized by adopting a long list of simplifying assumptions, the collection of which allow development of extremely efficient algorithms. However, when we develop algorithms for scientific computing (such as chemistry and biology) we are generally unable to make these assumptions without damaging the scientific validity of our results. Consequently, our best attempts at developing efficient algorithms often produce programs that still require weeks to run on standard desktop hardware; therefore, most computational biology labs, including ours, utilize high-speed computing resources in the form of compute clusters to obtain results more quickly. This proposal will help fund the computational infrastructure of our lab by providing a high-performance compute cluster with large disk storage, tape backup, and secure VPN connection.

我们的计算生物学小组的研究中心围绕高效计算技术的开发和应用，以解决生物医学科学（有机化学，生物化学和生物学）中的数据分析和建模问题。我们实验室的目标是产生在生物学上合理的标准下可证明正确的算法，并且对实验噪声和缺失数据具有鲁棒性。我们研究有机分子，从DNA（生命的分子蓝图），到小配体（具有数十个原子的药学上有趣的分子），再到大蛋白质（具有数千个原子的巨大分子）。我们感兴趣的是表征这些分子的结构和功能，然后利用这些信息来帮助我们的生物合作者开发新的药物和疾病模型。在计算机科学中，问题通常通过采用一长串简化假设来净化，这些假设的集合允许开发非常有效的算法。然而，当我们为科学计算（如化学和生物学）开发算法时，我们通常无法在不损害结果的科学有效性的情况下做出这些假设。因此，我们在开发高效算法方面的最佳尝试通常会产生仍然需要数周才能在标准桌面硬件上运行的程序;因此，包括我们在内的大多数计算生物学实验室都以计算集群的形式利用高速计算资源来更快地获得结果。该提案将通过提供具有大型磁盘存储、磁带备份和安全VPN连接的高性能计算集群，为我们实验室的计算基础设施提供资金。