MARC - DEVELOPING BIOINFORMATICS PROGRAMS, JULY 2009

这个子项目是利用资源的许多研究子项目之一。 由NIH/NCRR资助的中心拨款提供。对子项目的主要支持 子项目的首席调查员可能是由其他来源提供的， 包括美国国立卫生研究院的其他来源。为子项目列出的总成本可能 表示该子项目使用的中心基础设施的估计数量， 不是由NCRR赠款提供给次级项目或次级项目工作人员的直接资金。 暑期生物信息学学院是一门为期两周的课程，面向MARC项目机构的教职员工。暑期学院的目标是让参与者为在当地校园教授生物信息学课程做好准备。与MARC计划机构相关的感兴趣的个人被鼓励申请，包括来自不同系的教师，包括生物、化学、物理、数学、统计学、计算机科学和工程学。 研讨会将向与会者介绍围绕生物信息学的计算、数学和生物学问题。将讨论生物信息学中的一些基本主题，包括推断结构和功能；数据库搜索和成对序列比对；多序列比对；模式识别。将特别强调参数的选择，以及提出的算法和方法的数学、统计学和生物学基础。还将提供关于隐马尔可夫模型、高级特定位置权重矩阵、贝叶斯估计、同源建模、结构生物学、分子动力学模拟以及系统发育树创建和评估的信息。此外，还将讨论互联网资源和远程计算设施的使用，以及面向非生物学家的《生物学导论》和面向生物学家的Perl编程语言简介。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. The Summer Institute in Bioinformatics is a two-week course, directed towards faculty, students and staff at MARC program institutions. The Summer Institute has the goal of preparing the participants to teach bioinformatics courses at their local campuses. Interested individuals associated with a MARC program institution are encouraged to apply, including faculty from diverse departments, including biology, chemistry, physics, mathematics, statistics, computer science, and engineering. The workshop will introduce participants to the computational, mathematical and biological issues surrounding bioinformatics. A number of fundamental topics in bioinformatics will be discussed including inferring structures and functions; database searching and pairwise sequence alignment; multiple sequence alignments; pattern identification. Special emphasis will be placed on parameter selection, and the mathematical, statistical, and biological foundations of the algorithms and methods presented. Information will also be provided on hidden Markov models, advanced position-specific weight matrices, bayesian estimation, homology modeling, structural biology, molecular dynamics simulations, and phylogenic tree creation and evaluation. The use of internet resources and remote computing facilities will also be discussed as will an introduction Biology for non-biologists and an introduction to the PERL programming language for biologists.