本课程是生物信息学专项课程专项课程的一部分

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Pavel Pevzner 另外 +1 位授课教师

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生物信息学专项课程加州大学圣地亚哥分校

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In previous courses in the Specialization, we have discussed how to sequence and compare genomes. This course will cover advanced topics in finding mutations lurking within DNA and proteins.
In the first half of the course, we would like to ask how an individual's genome differs from the "reference genome" of the species. Our goal is to take small fragments of DNA from the individual and "map" them to the reference genome.  We will see that the combinatorial pattern matching algorithms solving this problem are elegant and extremely efficient, requiring a surprisingly small amount of runtime and memory.

In the second half of the course, we will learn how to identify the function of a protein even if it has been bombarded by so many mutations compared to similar proteins with known functions that it has become barely recognizable.  This is the case, for example, in HIV studies, since the virus often mutates so quickly that researchers can struggle to study it.  The approach we will use is based on a powerful machine learning tool called a hidden Markov model.

Finally, you will learn how to apply popular bioinformatics software tools applying hidden Markov models to compare a protein against a related family of proteins.

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第 6 门课程（共 7 门）

生物信息学专项课程

初级

完成时间大约为24 小时

英语（English）

字幕：阿拉伯语（Arabic）, 法语（French）, （欧洲人讲的）葡萄牙语, 意大利语, 越南语, 德语（German）, 俄语（Russian）, 英语（English）, 西班牙语（Spanish）

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第 6 门课程（共 7 门）

生物信息学专项课程

初级

完成时间大约为24 小时

英语（English）

授课教师

Pavel Pevzner

Professor

Department of Computer Science and Engineering

611,237 个学生

14 门课程

Phillip Compeau

Visiting Researcher

Department of Computer Science & Engineering

196,016 个学生

8 门课程

提供方

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.

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周 1

完成时间为 4 小时

Week 1: Introduction to Read Mapping

Welcome to our class! We are glad that you decided to join us.In this class, we will consider the following two central biological questions (the computational approaches needed to solve them are shown in parentheses):<ol><li>How Do We Locate Disease-Causing Mutations? (Combinatorial Pattern Matching)</li><li>Why Have Biologists Still Not Developed an HIV Vaccine? (Hidden Markov Models)</li></ol>As in previous courses, each of these two chapters is accompanied by a Bioinformatics Cartoon created by talented artist Randall Christopher and serving as a chapter header in the Specialization's bestselling <a href="http://bioinformaticsalgorithms.com" target="_blank">print companion</a>. You can find the first chapter's cartoon at the bottom of this message. <img src="https://stepic.org/media/attachments/lessons/292/chapter7_cropped.jpg" title="Image: https://stepic.org/media/attachments/lessons/292/chapter7_cropped.jpg" width="528">

完成时间为 4 小时

4 个视频（总计 33 分钟）, 2 个阅读材料, 3 个测验

周

周 2

完成时间为 4 小时

Week 2: The Burrows-Wheeler Transform

Welcome to week 2 of the class!

完成时间为 4 小时

3 个视频（总计 21 分钟）, 1 个阅读材料, 2 个测验

周

周 3

完成时间为 4 小时

Week 3: Speeding Up Burrows-Wheeler Read Mapping

Welcome to week 3 of class!

完成时间为 4 小时

4 个视频（总计 22 分钟）, 1 个阅读材料, 3 个测验

周

周 4

完成时间为 4 小时

Week 4: Introduction to Hidden Markov Models

Welcome to week 4 of class!

This week, we will start examining the case of aligning sequences with many mutations -- such as related genes from different HIV strains -- and see that our problem formulation for sequence alignment is not adequate for highly diverged sequences. To improve our algorithms, we will introduce a machine-learning paradigm called a hidden Markov model and see how dynamic programming helps us answer questions about these models.

完成时间为 4 小时

5 个视频（总计 42 分钟）

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来自发现 DNA 和蛋白质的突变（生物信息学 VI）的热门评论

由 TK 提供Jun 28, 2016

One of the best specialization on Coursera. Highly recommended for anyone who wants to apply his/her programming skills to fascinating real-world problems.

由 EJ 提供Jul 31, 2021

Great course! It opened my mind on the capabilities of algorithms beyond its intended purpose.

由 SC 提供Sep 15, 2018

Really enjoyed this course. It was great to get to build on work from previous courses.

由 RG 提供Apr 13, 2020

It was probably my favorite in this specialization (at least, out of first six).

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关于生物信息学专项课程

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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发现 DNA 和蛋白质的突变（生物信息学 VI）

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