Combinatorial algorithms in bioinformatics

生物信息学中的组合算法

• 批准号: 105809-2011
• 负责人: Gupta, Arvind
• 金额: $ 1.75万
• 依托单位: University of British Columbia
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=569115
• 关键词: Combinatorial; algorithms; bioinformatics

One of the great scientific feats of the 20th century is the understanding of the quantitative nature of biological systems. The resulting explosion of information has challenged scientists to develop novel in-silico tools to model, analyze, and infer the underlying processes. Dubbed bioinformatics, the result is a multi-disciplinary effort bringing together mathematics and computer scientists with biologists and chemists. My long-term research interest on algorithms for analyzing combinatorial structures has, over the past ten years, increasingly centered on cellular processes; problems my lab is considering include: 1. Haplotypes give the structure of individual chromosomes and as such are the basis for genetic disease susceptibility. In-vitro techniques are prohibitively expensive for determining individual haplotypes and our focus is on the development of efficient computational tools. 2. Drug synthesis, an expensive endevour, is now turning to computational tools. Our long-term project on Inverse Protein Folding attempts to construct a desired protein given information about the protein's properties. Such proteins are the basis for novel drug design as they will exhibit pre-determined behaviour. 3. We have developed a novel technique to cluster extremely large high-throughput data and used it for flow cytometry data. The result is a general purpose tool that can, for example, identify populations of cells that express similar intercellular or surface proteins. We are interested in the efficiency and efficacy of algorithms in real-life settings. Students graduating from my lab have a mix of life-sciences and computational skills, a combination sought out by industry and academia.

20世纪的伟大科学成就之一是对生物系统的定量性质的理解。由此产生的信息爆炸挑战了科学家们开发新的计算机工具来建模，分析和推断潜在的过程。被称为生物信息学，其结果是一个多学科的努力汇集了数学和计算机科学家与生物学家和化学家。在过去的十年里，我对分析组合结构的算法的长期研究兴趣越来越多地集中在细胞过程上;我的实验室正在考虑的问题包括： 1.单倍型给出了个体染色体的结构，因此是遗传疾病易感性的基础。体外技术是昂贵的，无法确定个人的单倍型，我们的重点是发展有效的计算工具。 2.药物合成是一项昂贵的工作，现在正转向计算工具。我们的反向蛋白质折叠的长期项目试图构建一个所需的蛋白质给定的信息，蛋白质的属性。这些蛋白质是新型药物设计的基础，因为它们将表现出预定的行为。 3.我们已经开发了一种新的技术来聚类极大的高通量数据，并将其用于流式细胞术数据。其结果是一个通用的工具，例如，可以识别表达相似的细胞间或表面蛋白的细胞群。 我们感兴趣的是算法在现实生活中的效率和功效。从我的实验室毕业的学生拥有生命科学和计算技能的混合体，这是工业界和学术界所寻求的组合。