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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/assembling-genomes
课程评论：没有评论
课程名称：基因组组装编程挑战 课程概述： 2011年春季，德国爆发了一场致命的疾病，最初表现为食物中毒和血性腹泻，最终导致肾衰竭。此次疫情是近期历史上最致命的疫情，病原体为一种神秘的细菌株，称为E. coli X。随着疫情的发展，德国官员将疫情与吕贝克的一家餐馆联系在一起，近20%的就餐者在一周内出现了血性腹泻。此时，生物学家意识到面临着一种未知病原体，传统方法不足以应对，需要计算生物学家的帮助来组装和分析新出现病原体的基因组。 为了调查疫情菌株的进化起源和致病潜力，研究人员启动了众包研究项目，发布了一名患者的细菌DNA测序数据，引发了全球计算生物学家的分析热潮。甚至还利用了GitHub平台进行项目协作。 本在线课程将让你跟随调查此次疫情的生物信息学家，开发一个程序来组装E. coli X的基因组，该基因组由数百万个重叠的DNA子串组成。 课程大纲： 1. **2011年欧洲E. coli疫情** - 描述：2011年4月，德国医院里数百人因致命疾病住院，病症多为食物中毒和血性腹泻。这场疫情感染了游客，并导致53人死亡。全球计算生物学家需要解决的问题是“E. coli X的基因组序列是什么？”以便揭示其致病性基因。在该模块中，您将学习基本的基因组概念，并先解决一个简单的小病毒组装问题。 2. **使用de Bruijn图组装基因组** - 描述：1977年，DNA测序方法使得小病毒的组装成为可能，该方法经历了一系列转变，促进了个性化医学的发展。您将了解利用DNA阵列提供的短k-mer信息进行DNA测序的算法挑战，并回顾18世纪的柯尼斯堡桥问题，解决与拼图组装相关的挑战。 3. **基因组组装面临真实的测序数据** - 描述：我们之前的讨论基于多种假设，本模块将面对现代测序技术带来的实际挑战，并探讨针对这些挑战而开发的一些算法技术。之后，您将组装寄生在叶蝉体内的最小细菌基因组，该基因组仅约112,091个核苷酸和137个基因。完成这些后，您将准备组装E. coli X的基因组。 通过这一系列学习，您将深入理解基因组组装的计算过程，并为实际应用提供必要的编程技能。
Name:The 2011 European E. coli Outbreak
Description:In April 2011, hundreds of people in Germany were hospitalized with a deadly disease that often started as food poisoning with bloody diarrhea. It was the beginning of the deadliest outbreak in recent history, caused by a mysterious bacterial strain that we will refer to as E. coli X. Within a few months, the outbreak had infected thousands and killed 53 people. To prevent the further spread of the outbreak, computational biologists all over the world had to answer the question “What is the genome sequence of E. coli X?” in order to figure out what new genes it acquired to become pathogenic. The 2011 German outbreak represented an early example of epidemiologists collaborating with computational biologists to stop an outbreak. In this Genome Assembly Programming Challenge, you will follow in the footsteps of the bioinformaticians investigating the outbreak by developing a program to assemble the genome of the deadly E. coli X strain. However, before you embark on building a program for assembling the E. coli X strain, we have to explain some genomic concepts and warm you up by having you solve a simpler problem of assembling a small virus.
Name:Assembling Genomes Using de Bruijn Graphs
Description:DNA sequencing approach that led to assembly of a small virus in 1977 went through a series of transformations that contributed to the emergence of personalized medicine a few years ago. By the late 1980s, biologists were routinely sequencing viral genomes containing hundreds of thousands of nucleotides, but the idea of sequencing a bacterial (let alone the human) genome containing millions (or even billions) of nucleotides remained preposterous and would cost billions of dollars. In 1988, three biologists (independently and simultaneously!) came up with an idea to reduce sequencing cost and proposed the futuristic and at the time completely implausible method of DNA arrays. None of these three biologists could have possibly imagined that the implications of his own experimental research would eventually bring him face-to-face with challenging algorithmic problems. In this module you will learn about the algorithmic challenge of DNA sequencing using information about short k-mers provided by DNA arrays. You will also travel to the 18the century to learn about the Bridges of Konigsberg and solve a related problem of assembling a jigsaw puzzle!
Name:Genome Assembly Faces Real Sequencing Data
Description:Our discussion of genome assembly has thus far relied upon various assumptions. In this module, we will face practical challenges introduced by quirks in modern sequencing technologies and discuss some algorithmic techniques that have been devised to address these challenges. Afterwards, you will assemble the smallest bacterial genome that lives symbiotically inside leafhoppers. Its sheltered life has allowed it to reduce its genome to only about 112,091 nucleotides and 137 genes. And afterwards, you will be ready to assemble the E. coli X genome!
In Spring 2011, thousands of people in Germany were hospitalized with a deadly disease that started as food poisoning with bloody diarrhea and often led to kidney failure. It was the beginning of the deadliest outbreak in recent history, caused by a mysterious bacterial strain that we will refer to as E. coli X. Soon, German officials linked the outbreak to a restaurant in Lübeck, where nearly 20% of the patrons had developed bloody diarrhea in a single week. At this point, biologists knew that they were facing a previously unknown pathogen and that traditional methods would not suffice – computational biologists would be needed to assemble and analyze the genome of the newly emerged pathogen. To investigate the evolutionary origin and pathogenic potential of the outbreak strain, researchers started a crowdsourced research program. They released bacterial DNA sequencing data from one of a patient, which elicited a burst of analyses carried out by computational biologists on four continents. They even used GitHub for the project: https://github.com/ehec-outbreak-crowdsourced/BGI-data-analysis/wiki The 2011 German outbreak represented an early example of epidemiologists collaborating with computational biologists to stop an outbreak. In this online course you will follow in the footsteps of the bioinformaticians investigating the outbreak by developing a program to assemble the genome of the E. coli X from millions of overlapping substrings of the E.coli X genome.
