PSC BIOMED ROADSHOW: WORKSHOP AT TENNESSEE STATE UNIVERSITY APRIL 6 & 7, 2006

这个子项目是许多研究子项目中的一个 由NIH/NCRR资助的中心赠款提供的资源。子项目和 研究者（PI）可能从另一个NIH来源获得了主要资金， 因此可以在其他CRISP条目中表示。所列机构为 研究中心，而研究中心不一定是研究者所在的机构。 田纳西州立大学生物科学系和匹兹堡超级计算中心的生物医学超级计算国家资源 这个为期两天的研讨会旨在教授田纳西州立大学的研究人员序列分析的基础知识。研讨会参与者将学习如何使用匹兹堡超级计算中心（PSC）超级计算机上的序列分析工具。讲座将由亚历克斯·罗佩莱夫斯基、大卫·迪尔菲尔德和休·尼古拉斯主持。计算机实验室会议将遵循每一个讲座。每个参与者将在PSC收到一个帐户，使他们能够试验整个研讨会所描述的技术。下面描述的四个主题中的每一个都将在计算机实验室会议之后的讲座中讨论： Internet上的生物信息学和序列分析资源 互联网和万维网的出现大大增加了实验生物学家可用的信息和计算资源的可用性。本讲座将介绍一些可用的在线资源，包括匹兹堡超级计算中心的资源和服务。我们还将讨论如何使用的CNOSS软件，以及如何定位和检索指定的序列从序列数据库。 数据库对齐和成对对齐 本讲座介绍了序列比较的数学和生物学基础。也就是说，讲座将详细描述各种序列比对算法，包括近似中所做的化学（例如，FASTA和BLAST）来减少计算时间，而不是用严格的算法（例如，Needleman-Wunsch，Smith-Waterman）。讲座还将描述当前使用的相似性矩阵的基本数学和生物学基础，以及如何正确使用这些表格。预期的目标是为研究人员提供必要的背景信息的搜索协议，使他们放心，在他们的数据库搜索做出良好的选择，并了解天真地使用数据库搜索工具的缺点。 多序列比对 这堂课涵盖了几个序列的整体比对（全局比对）以及全局比对如何与潜在的生物遗传学相关。在讲座中，我们将描述每个多比对程序的数学和生物学基础，并展示每种方法的固有弱点（例如，ClustalW、MSA或T-COFFEE）。 发现未比对序列中的诊断模式和基序 参与者将被介绍到图案和模式，以及它们通常表示的各种格式，包括共识残基，正则表达式，隐马尔可夫模型和权重矩阵。讨论了方法available确定短，以及保守的本地模式，如启动子序列或催化位点。还讨论了轮廓分析和期望最大化技术。 参与者信息：本次研讨会的当地联系人是Terrance L博士。约翰逊，部门，大津，tjohnson@tnstate.edu，615-963-5681。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The Department of Biological Sciences at Tennessee State University and Pittsburgh Supercomputing Center's National Resource for Biomedical Supercomputing This two-day workshop is designed to teach researchers at Tennessee State University the basics of sequence analysis. Workshop participants will learn how to use tools for sequence analysis on the supercomputers at Pittsburgh Supercomputing Center (PSC). Lectures will be led by Alex Ropelewski, David Deerfield, and Hugh Nicholas. Computer laboratory sessions will follow each lecture. Each participant will receive an account at the PSC to allow them to experiment with the techniques described throughout the workshop. Each of the four topics described below will be covered in a lecture followed by a computer laboratory session: Bioinformatics and Sequence Analysis Resources on the Internet The advent of the Internet and the World Wide Web has substantially increased the availability of information and computational resources available to experimental biologists. This lecture will describe a number of online resources available, including resources and services availiable at the Pittsburgh Supercomputing Center. We will also discuss the use of the EMBOSS software and how to locate and retreive specified sequences from a sequence database. Database Searches and Pairwise Alignments This lecture presents both the mathematical and biological foundations of sequence comparison. That is, the lecture will describe in detail the various sequence alignment algorithms including the approximations made in the heuristics (e.g., FASTA and BLAST) to decrease computational time as opposed to searches with a rigorous algorithms (e.g., Needleman-Wunsch, Smith-Waterman). The lecture will also describe the underlying mathematical and biological bases for the similarity matrices in current use and how these tables should be properly used. The intended goal is to provide a researcher with the necessary background information about the search protocols so that they are assured of making good choices in their database searches and understand the shortcomings of naively using a database searching tool. Multiple Sequence Alignments This lecture covers aligning several sequences in their entirety (global alignments) and how global alignments are related to underlying biological phylogenies. During the lecture, we will describe the mathematical and biological basis for each of the multiple alignment programs and demonstrate the inherent weaknesses in each approach (e.g., ClustalW, MSA, or T-COFFEE). Discovering Diagnostic Patterns and Motifs in Unaligned Sequences Participants will be introduced to motifs and patterns and the various formats in which they are commonly represented, including consensus residues, regular expressions, hidden Markov Models and weight matrices. Discusses methods availiable to identify short, well conserved local patterns, such as promoter sequences or catalytic sites. Also discusses profile analysis and expectation maximization techniques. Participant Information: The local contact for this workshop is Dr. Terrance L. Johnson, Dept. of Biological Sciences, TSU, tjohnson@tnstate.edu, 615-963-5681.