生物信息学顶点项目:生物学中的大数据

Bioinformatics Capstone: Big Data in Biology

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加州大学圣地亚哥分校
Coursera
  • 完成时间大约为 15 个小时
  • 初级
  • 英语
注:本课程由Coursera和Linkshare共同提供,因开课平台的各种因素变化,以上开课日期仅供参考

课程概况

In this course, you will learn how to use the BaseSpace cloud platform developed by Illumina (our industry partner) to apply several standard bioinformatics software approaches to real biological data.

In particular, in a series of Application Challenges will see how genome assembly can be used to track the source of a food poisoning outbreak, how RNA-Sequencing can help us analyze gene expression data on the tissue level, and compare the pros and cons of whole genome vs. whole exome sequencing for finding potentially harmful mutations in a human sample.

Plus, hacker track students will have the option to build their own genome assembler and apply it to real data!

课程大纲

Week 1: Identifying the Culprit in a Food Poisoning Outbreak

This week, we will apply genome sequencing algorithms to identify the bacterium causing a deadly food poisoning outbreak.

Week 2: Comparing Gene Expression in Tissue Samples with RNA-Seq

In this week's Application Challenge, we will learn how RNA-Sequencing can be applied to perform tissue-level gene expression analysis. In particular, which is more similar on a gene expression level: different tissues from the same organism, or analogous tissues from related species? This question was the subject of recent debate and a Twitter controversy -- read more to find out!

Week 3: Weighing the Pros and Cons of Whole Genome and Whole Exome Sequencing on a Human Sample

Comparing the differences between sequencing an entire human genome and sequencing only the exome, or the DNA that is eventually translated into protein. Can we obtain a complete picture of someone's genetic disease predispositions from only the exome, or is there information lurking in introns that can provide doctors with vital information? How do we weigh the trade-offs when considering genome and exome sequencing?

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