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!
提供方
教學大綱 - 您將從這門課程中學到什麼
週
1完成時間為 5 小時
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.
4 個閱讀材料, 1 個測驗
4 個閱讀材料
Welcome to Class!10分鐘
Special Thanks2分鐘
Introduction15分鐘
Databases and Tools5分鐘
週
2完成時間為 4 小時
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!
2 個閱讀材料, 1 個測驗
2 個閱讀材料
Introduction15分鐘
Databases and Tools5分鐘
週
3完成時間為 5 小時
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?
4 個閱讀材料, 1 個測驗
4 個閱讀材料
Introduction15分鐘
Databases and Tools10分鐘
Walkthroughs15分鐘
Reading: Part 3 FAQs
4.6
4 個審閱33%
完成這些課程後已開始新的職業生涯
33%
通過此課程獲得實實在在的工作福利
來自Bioinformatics Capstone: Big Data in Biology的熱門評論
I hope that the links to access data in the peer graded assignments gets fixed soon!
講師
Phillip Compeau
Visiting ResearcherDepartment of Computer Science & Engineering
Pavel Pevzner
ProfessorDepartment of Computer Science and Engineering
關於 加州大学圣地亚哥分校
UC San Diego is an academic powerhouse and economic engine, recognized as one of the top 10 public universities by U.S. News and World Report. Innovation is central to who we are and what we do. Here, students learn that knowledge isn't just acquired in the classroom—life is their laboratory.
關於 生物信息学 專項課程
Join Us in a Top 50 MOOC of All Time!
How do we sequence and compare genomes? How do we identify the genetic basis for disease? How do we construct an evolutionary Tree of Life for all species on Earth?
When you complete this Specialization, you will learn how to answer many questions in modern biology that have become inseparable from the computational approaches used to solve them. You will also obtain a toolkit of existing software resources built on these computational approaches and that are used by thousands of biologists every day in one of the fastest growing fields in science.
Although this Specialization centers on computational topics, you do not need to know how to program in order to complete it. If you are interested in programming, we feature an "Honors Track" (called "hacker track" in previous runs of the course). The Honors Track allows you to implement the bioinformatics algorithms that you will encounter along the way in dozens of automatically graded coding challenges. By completing the Honors Track, you will be a bioinformatics software professional!
Learn more about the Bioinformatics Specialization (including why we are wearing these crazy outfits) by watching our introductory video.
You can purchase the Specialization's print companion, Bioinformatics Algorithms: An Active Learning Approach, from the textbook website.
Our first course, "Finding Hidden Messages in DNA", was named a top-50 MOOC of all time by Class Central!
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