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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/comparing-genomes
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课程名称：比较基因、蛋白质和基因组（生物信息学 III） 课程概述：在之前的课程中，我们已对基因组进行了测序，现在我们将学习如何比较这些基因组，以确定物种的进化过程及其差异。课程的前半部分将比较两段短的生物序列，例如基因（即短的DNA序列）或蛋白质。我们将接触到一种强大的算法工具——动态规划，用于确定两个基因/蛋白质之间的突变数量。 课程后半部分将扩大视角，比较整个基因组，观察大规模突变，称为基因组重排，这是在数百万年的进化中，DNA大块区域发生剧烈变化的过程。通过对人类和小鼠基因组的研究，我们会探讨基因组中是否存在“脆弱”的区域，这些区域更容易由于基因组重排而断裂。我们将看到组合算法如何帮助我们回答这一问题。 最后，您将学习如何应用流行的生物信息学软件工具，解决序列比对中的问题，包括BLAST。 课程大纲： 第一周：序列比对简介 - 本周将探讨如何比较DNA和氨基酸序列，引入序列比对的基本概念，并使用动态规划算法。 第二周：从寻找最长路径到比对DNA字符串 - 学习如何找到两字符串的最高得分比对，阐释比对问题与有向无环图中寻找最长路径的关联。 第三周：序列比对的高级主题 - 讨论在比对长字符串时，如何提高算法的内存效率，以及如何处理多个字符串比对的问题。 第四周：基因组重排与脆弱性 - 探讨如何比较整个基因组及其重排现象，计算连接两个物种的进化路径上的重排次数。 第五周：应用基因组重排分析寻找基因组脆弱性 - 继续探讨如何计算基因组之间的距离，以及这种计算如何帮助我们理解基因组的脆弱区域。 第六周：生物信息学应用挑战 - 在课程的最后一周，应用序列比对算法推断非核糖体代码的内容。 通过这一课程，您将深入理解生物序列比对的原理及其在生物信息学中的应用。
Name:Week 1: Introduction to Sequence Alignment
Description:
Welcome to class!
If you joined us in the previous course in this Specialization, then you became an expert at assembling genomes and sequencing antibiotics. The next natural question to ask is how to compare DNA and amino acid sequences. This question will motivate this week's discussion of sequence alignment, which is the first of two questions that we will ask in this class (the algorithmic methods used to answer them are shown in parentheses):
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 print companion. You can find the first chapter's cartoon at the bottom of this message. Why have taxis suddenly become free of charge in Manhattan? Where did Pavel get so much spare change? And how should you get dressed in the morning so that you aren't late to your job as a crime-stopping superhero? Answers to these questions, and many more, in this week's installment of the course.
Name:Week 2: From Finding a Longest Path to Aligning DNA Strings
Description:
Welcome to Week 2 of the class!
Last week, we saw how touring around Manhattan and making change in a Roman shop help us find a longest common subsequence of two DNA or protein strings.
This week, we will study how to find a highest scoring alignment of two strings. We will see that regardless of the underlying assumptions that we make regarding how the strings should be aligned, we will be able to phrase our alignment problem as an instance of finding the longest path in a directed acyclic graph.
Name:Week 3: Advanced Topics in Sequence Alignment
Description:
Welcome to Week 3 of the class!
Last week, we saw how a variety of different applications of sequence alignment can all be reduced to finding the longest path in a Manhattan-like graph.
This week, we will conclude the current chapter by considering a few advanced topics in sequence alignment. For example, if we need to align long strings, our current algorithm will consume a huge amount of memory. Can we find a more memory-efficient approach? And what should we do when we move from aligning just two strings at a time to aligning many strings?
Name:Week 4: Genome Rearrangements and Fragility
Description:
Welcome to Week 4 of the class!
You now know how to compare two DNA (or protein) strings. But what if we wanted to compare entire genomes? When we "zoom out" to the genome level, we find that substitutions, insertions, and deletions don't tell the whole story of evolution: we need to model more dramatic evolutionary events known as genome rearrangements, which wrench apart chromosomes and put them back together in a new order. A natural question to ask is whether there are "fragile regions" hidden in your genome where chromosome breakage has occurred more often over millions of years. This week, we will begin addressing this question by asking how we can compute the number of rearrangements on the evolutionary path connecting two species.
You can find this week's Bioinformatics Cartoon from Randall Christopher at the bottom of this E-mail. What do earthquakes and a stack of pancakes have to do with species evolution? Keep learning to find out!
Name:Week 5: Applying Genome Rearrangement Analysis to Find Genome Fragility
Description:
Last week, we asked whether there are fragile regions in the human genome. Then, we took a lengthy detour to see how to compute a distance between species genomes, a discussion that we will continue this week.
It is probably unclear how computing the distance between two genomes can help us understand whether fragile regions exist. If so, please stay tuned -- we will see that the connection between these two concepts will yield a surprising conclusion to the class.
Name:Week 6: Bioinformatics Application Challenge
Description:In the sixth and final week of the course, we will apply sequence alignment algorithms to infer the non-ribosomal code.
Once we have sequenced genomes in the previous course, we would like to compare them to determine how species have evolved and what makes them different. In the first half of the course, we will compare two short biological sequences, such as genes (i.e., short sequences of DNA) or proteins. We will encounter a powerful algorithmic tool called dynamic programming that will help us determine the number of mutations that have separated the two genes/proteins. In the second half of the course, we will "zoom out" to compare entire genomes, where we see large scale mutations called genome rearrangements, seismic events that have heaved around large blocks of DNA over millions of years of evolution. Looking at the human and mouse genomes, we will ask ourselves: just as earthquakes are much more likely to occur along fault lines, are there locations in our genome that are "fragile" and more susceptible to be broken as part of genome rearrangements? We will see how combinatorial algorithms will help us answer this question. Finally, you will learn how to apply popular bioinformatics software tools to solve problems in sequence alignment, including BLAST.
