CSHL Computational and Comparative Genomics Course

描述(申请人提供)：冷泉港实验室拟于2014-2016年秋季继续开设《计算与比较基因组学》课程。计算和比较基因组学课程为分子生物学、遗传学和生物化学领域的实验生物学家提供必要的理论背景和实践经验，以使用和评估基因组注释和分析的计算方法，包括蛋白质序列数据库搜索、多序列比对、启动子和其他基因调控元件的识别，以及将序列信息整合到更广泛的生物功能模型中。本课程还向计算机科学家和数学家介绍生物序列分析和计算生物学中涉及的算法、计算方法和生物学问题。对于博士后研究员，以及有兴趣将他们的研究方向转向计算生物学的初级和高级研究人员，本课程提供了计算生物学方法的介绍和对未来方向的概述。在为期七天的时间里，学生们将在基因组分析的生物和计算机科学基础以及具有挑战性问题的实际计算机实验室经验方面获得坚实的基础。这门课程由该领域的国际公认的领导者授课，他们提供他们开发的项目和生物数据库的动手演示。在课程结束时，学生不仅可以有效地使用生物序列分析中现有的工具，他们还可以通过考虑替代方法和解释来评估新的计算方法，并欣赏计算方法在回答广泛的生物学问题方面的优势和局限性。

DESCRIPTION (provided by applicant): The Cold Spring Harbor Laboratory proposes to continue a course entitled "Computational and Comparative Genomics", to be held in the fall of 2014 - 2016. The Computational and Comparative Genomics course provides experimental biologists with backgrounds in molecular biology, genetics, and biochemistry with the theoretical background and practical experience necessary to use and evaluate computational approaches to genome annotation and analysis, including protein sequence database searching, multiple sequence alignment, identification of promoters and other genetic regulatory elements, and the integration of sequence information into broader models of biological function. The course also provides computer scientists and mathematicians with an introduction to the algorithms, computational methods, and biological problems that are addressed in biological sequence analysis and computational biology. For post-doctoral fellows, and junior and senior investigators who are interested in changing their research direction towards computational biology, the course provides an introduction to computational biology methods and a survey of future directions. Over a seven day period, the students receive a strong grounding in the both the biological and computer science foundations for genome analysis and practical computer laboratory experience on challenging problems. The course is taught by internationally recognized leaders in the field, who provide hands-on demonstrations of the programs and biological databases they have developed. At the end of the course, students can not only use effectively currently available tools in biological sequence analysis, they can also evaluate critically new computational approaches by considering alternative methods and interpretations, and appreciate the strengths and limitations of computational methods for answering broad biological questions.