生物信息学方法 I

Bioinformatic Methods I

使用主要来自网络的程序分析生物学数据。这是一门概论性课程,强调动手实践能力。我们会介绍一些理论,但我们主要关注的是使用已有生物信息学工具来分析数据并得到生物学假设。

多伦多大学

Coursera

计算机

简单(初级)

13 小时

本课程由Coursera和Linkshare共同提供
  • 英语
  • 3441

课程概况

大规模生物项目,例如使用RNA-seq、微阵列等技术的人类基因组测序和基因表达分析,为生物学家建立了丰富的数据资源。然而,科学界所面临的真正挑战是分析这些数据并提取有用信息。这门课将关注已有生物信息学资源的利用,主要是网络程序和数据库,以此访问丰富数据资源,来回答一般生物学工作者所关心的问题,这门课的动手实践性很强。

主题包括多序列比对、系统发生学、基因表达数据分析、蛋白质相互作用网络。这些内容将分为两个部分。

第一部分是生物信息学方法I,涵盖数据库、Blast、多序列比对、系统发生学、选择分析、RNA-seq和元基因组学。

第二部分是生物信息学方法II,涵盖基序搜索、蛋白-蛋白相互作用、结构生物信息学、基因表达数据分析、顺式元件预测。

这两门课对任何考虑读生物科学或分子医学研究生的学生会很有帮助。

Large-scale biology projects such as the sequencing of the human genome and gene expression surveys using RNA-seq, microarrays and other technologies have created a wealth of data for biologists. However, the challenge facing scientists is analyzing and even accessing these data to extract useful information pertaining to the system being studied. This course focuses on employing existing bioinformatic resources – mainly web-based programs and databases – to access the wealth of data to answer questions relevant to the average biologist, and is highly hands-on.

Topics covered include multiple sequence alignments, phylogenetics, gene expression data analysis, and protein interaction networks, in two separate parts.

The first part, Bioinformatic Methods I (this one), deals with databases, Blast, multiple sequence alignments, phylogenetics, selection analysis and metagenomics.

The second part, Bioinformatic Methods II, covers motif searching, protein-protein interactions, structural bioinformatics, gene expression data analysis, and cis-element predictions.

This pair of courses is useful to any student considering graduate school in the biological sciences, as well as students considering molecular medicine. Both provide an overview of the many different bioinformatic tools that are out there.

These courses are based on one taught at the University of Toronto to upper-level undergraduates who have some understanding of basic molecular biology. If you’re not familiar with this, something like https://learn.saylor.org/course/bio101 might be helpful. No programming is required for this course.

你将学到什么

Genetic Analysis

Bioinformatics Analysis

Evolution

Comparative Genomics

课程大纲

第1周:NCBI/Blast I
第2周:Blast II/比较基因组学
第3周:多序列比对
第4周:系统发生学
第5周:选择分析
第6周:“下一代”序列分析(RNA-seq)/元基因组学

预备知识

建议学生拥有一些分子生物学知识,例如修过大二水平该主题的概论课程。

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