Bioinformatic Methods II

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课程主页: https://www.coursera.org/archive/bioinformatics-methods-2

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课程简介

University of Toronto

课程大纲

In this module we'll be exploring conserved regions within protein families. Such regions can help us understand the biology of a sequence, in that they are likely important for biological function, and also be used to help ascribe function to sequences where we can't identify any homologs in the databases. There are various ways of describing the conserved regions from simple regular expressions to profiles to profile hidden Markov models (HMMs).

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课程详情

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, dealt with databases, Blast, multiple sequence alignments, phylogenetics, selection analysis and metagenomics. This, the second part, Bioinformatic Methods II, will cover 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. 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 although some command line work (though within a web browser) occurs in the 5th module. Bioinformatic Methods II is regularly updated, and was last updated for March 2019.

生物信息学方法II:大规模生物学项目,例如使用RNA-seq,微阵列和其他技术进行的人类基因组测序和基因表达调查,为生物学家创造了大量数据。但是,科学家面临的挑战是分析甚至访问这些数据以提取与正在研究的系统有关的有用信息。本课程侧重于利用现有的生物信息资源(主要是基于Web的程序和数据库)来访问大量数据,以回答与普通生物学家有关的问题,并且非常动手。 涵盖的主题包括两个独立的部分中的多个序列比对,系统发育,基因表达数据分析和蛋白质相互作用网络。 第一部分,生物信息学方法I,涉及数据库,Blast,多重序列比对,系统发育,选择分析和宏基因组学。 这是第二部分,生物信息学方法II,将涵盖主题搜索,蛋白质-蛋白质相互作用,结构生物信息学,基因表达数据分析和顺式元素预测。 这两门课程对所有考虑攻读生物科学研究生院的学生以及考虑分子医学的学生都非常有用。 这些课程是基于多伦多大学教授的一门课程,面向对基本分子生物学有一定了解的高级本科生。如果您不熟悉此方法,则可能会有用如https://learn.saylor.org/course/bio101。尽管第5个模块中发生了一些命令行工作(尽管在Web浏览器中),但本课程不需要编程。 生物信息学方法II定期进行更新,最后更新于2019年3月。

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