Combinatorial algorithms in bioinformatics

20世纪最伟大的科学壮举之一是对生物系统的量化本质的理解。由此产生的信息爆炸向科学家们提出了挑战，要求他们开发新的硅胶工具来模拟、分析和推断潜在的过程。被称为生物信息学的成果是一项多学科的努力，将数学和计算机科学家与生物学家和化学家结合在一起。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，因此是遗传病易感性的基础。体外技术对于确定个体单倍型来说是昂贵得令人望而却步的，我们的重点是开发高效的计算工具。 2.药物合成是一项昂贵的任务，现在正转向计算工具。我们关于反向蛋白质折叠的长期项目试图在已知蛋白质性质的情况下构建所需的蛋白质。这些蛋白质是新药设计的基础，因为它们将表现出预先确定的行为。 3.我们开发了一种新的技术来聚类超大数据量的高通量数据，并将其用于流式细胞仪数据。其结果是一种通用的工具，例如，可以识别表达类似细胞间或表面蛋白的细胞群体。 我们感兴趣的是算法在现实生活中的效率和效力。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，这是工业界和学术界寻求的组合。

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.