CSHL Computational and Comparative Genomics Course

描述（申请人提供）：冷泉港实验室拟开设“计算与比较基因组学”课程，授课时间为2014 - 2016年秋季。计算与比较基因组学课程为具有分子生物学、遗传学和生物化学背景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、启动子和其他遗传调控元件的鉴定。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。对于有兴趣将研究方向转向计算生物学的博士后研究员和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未来方向的调查。在为期7天的课程中，学生将在基因组分析的生物学和计算机科学基础方面获得坚实的基础，并在具有挑战性的问题上获得实际的计算机实验室经验。该课程由该领域国际公认的领导者讲授，他们提供他们开发的程序和生物数据库的实际演示。在课程结束时，学生不仅可以有效地使用当前可用的生物序列分析工具，还可以通过考虑替代方法和解释来批判性地评估新的计算方法，并了解计算方法在回答广泛的生物学问题时的优势和局限性。

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.