|
所在平台: Coursera |
课程主页: https://www.coursera.org/learn/dna-analysis
课程评论：没有评论
课程名称：DNA中的隐藏信息（生物信息学I） 课程概述：该课程被Class Central评选为有史以来前50名的MOOC课程之一！本课程是生物信息学系列课程的开端，展示了计算在现代生物学中的强大力量。您将无需穿上实验室外套，便可深入探索DNA中的隐藏信息。 在课程的前半部分，我们将研究DNA复制，并探讨基因组中DNA复制开始的位置。通过一些简单的算法，我们能够找到许多细菌的复制起始点。 课程的后半部分将聚焦于另外一个生物学问题——哪些DNA模式充当分子时钟。我们的身体细胞是如何维持昼夜节律的？这一次，我们将通过识别隐藏的信息，深入理解DNA的复杂语言。令人惊讶的是，我们将使用随机算法（通过掷骰子和抛硬币）来解决这些问题。 最后，您将亲自使用现有的软件工具，寻找与结核分枝杆菌在宿主内“休眠”多年后的活跃感染相关的基因中的生物学模式。 课程大纲： - 第一周：欢迎来到课堂！ - 本课程将聚焦于现代计算生物学的两个前沿问题，以及我们将用于解决这些问题的算法方法： 1. 第1-2周：DNA复制从何开始？（算法热身） 2. 第3-4周：哪些DNA模式充当分子时钟？（随机算法） - 第5周将进行生物信息学应用挑战，您将应用软件工具在真实的生物数据集中寻找DNA模式。 每个章节都有Randall Christopher创作的生物信息学漫画作为开篇，并伴随该专业化的畅销书。 课程结构： - 第二周：寻找复制起始点 - 第三周：寻找调节基因的模式 - 第四周：掷骰子如何帮助我们找到调节基因的模式 - 第五周：生物信息学应用挑战 加入我们，揭示生物学与隐藏信息之间的联系吧！
Name:Week 1: Welcome!
Description:
Welcome to class!
This course will focus on two questions at the forefront of modern computational biology, along with the algorithmic approaches we will use to solve them in parentheses:
Week 5 will consist of a Bioinformatics Application Challenge in which you will get to apply software for finding DNA motifs to a real biological dataset.
Each of the two chapters in the course is accompanied by a Bioinformatics Cartoon created by 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. What does a cryptic message leading to buried treasure have to do with biology? We hope you will join us to find out!
Phillip and Pavel
Name:Week 2: Finding Replication Origins
Description:
Welcome to Week 2 of class!
This week, we will examine the biological details of how DNA replication is carried out in the cell. We will then see how to use these details to help us design an intelligent algorithmic approach looking for the replication origin in a bacterial genome.
Name:Week 3: Hunting for Regulatory Motifs
Description:
Welcome to Week 3 of class!
This week, we begin a new chapter, titled "Which DNA Patterns Play the Role of Molecular Clocks?" At the bottom of this message is this week's Bioinformatics Cartoon. What does a late night casino trip with two 18th Century French mathematicians have in common with finding molecular clocks? Start learning to find out...
Name:Week 4: How Rolling Dice Helps Us Find Regulatory Motifs
Description:
Welcome to Week 4 of class!
Last week, we encountered a few introductory motif-finding algorithms. This week, we will see how to improve upon these motif-finding approaches by designing randomized algorithms that can "roll dice" to find motifs.
Name:Week 5: Bioinformatics Application Challenge
Description:Welcome to week 5 of the class! This week, we will apply popular motif-finding software in order to hunt for motifs in a real biological dataset.
Named a top 50 MOOC of all time by Class Central! This course begins a series of classes illustrating the power of computing in modern biology. Please join us on the frontier of bioinformatics to look for hidden messages in DNA without ever needing to put on a lab coat. In the first half of the course, we investigate DNA replication, and ask the question, where in the genome does DNA replication begin? We will see that we can answer this question for many bacteria using only some straightforward algorithms to look for hidden messages in the genome. In the second half of the course, we examine a different biological question, when we ask which DNA patterns play the role of molecular clocks. The cells in your body manage to maintain a circadian rhythm, but how is this achieved on the level of DNA? Once again, we will see that by knowing which hidden messages to look for, we can start to understand the amazingly complex language of DNA. Perhaps surprisingly, we will apply randomized algorithms, which roll dice and flip coins in order to solve problems. Finally, you will get your hands dirty and apply existing software tools to find recurring biological motifs within genes that are responsible for helping Mycobacterium tuberculosis go "dormant" within a host for many years before causing an active infection.
