Algorithms for DNA Sequencing
link 来源:www.coursera.org
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assignment 等级:入门
chat_bubble_outline 语言:英语
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关于内容

We will learn computational methods -- algorithms and data structures -- for analyzing DNA sequencing data. We will learn a little about DNA, genomics, and how DNA sequencing is used. We will use Python to implement key algorithms and data structures and to analyze real genomes and DNA sequencing datasets.

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课程大纲

  • Week 1 - DNA sequencing, strings and matching
    This module we begin our exploration of algorithms for analyzing DNA sequencing data. We'll discuss DNA sequencing technology, its past and present, and how it works.
  • Week 2 - Preprocessing, indexing and approximate matching
    In this module, we learn useful and flexible new algorithms for solving the exact and approximate matching problems. We'll start by learning Boyer-Moore, a fast and very widely used algorithm for exact matching
  • Week 3 - Edit distance, assembly, overlaps
    This week we finish our discussion of read alignment by learning about algorithms that solve both the edit distance problem and related biosequence analysis problems, like global and local alignment.
  • Week 4 - Algorithms for assembly
    In the last module we began our discussion of the assembly problem and we saw a couple basic principles behind it. In this module, we'll learn a few ways to solve the alignment problem.
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教师

Ben Langmead, PhD
Assistant Professor
Computer Science

Jacob Pritt

Department of Computer Science

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内容设计师

Johns Hopkins University
The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
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平台

Coursera

Coursera是一家数字公司,提供由位于加利福尼亚州山景城的计算机教师Andrew Ng和达芙妮科勒斯坦福大学创建的大型开放式在线课程。

Coursera与顶尖大学和组织合作,在线提供一些课程,并提供许多科目的课程,包括:物理,工程,人文,医学,生物学,社会科学,数学,商业,计算机科学,数字营销,数据科学 和其他科目。

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