Algorithms for DNA Sequencing

开始时间: 04/22/2022 持续时间: 4 weeks

所在平台: CourseraArchive

课程类别: 其他类别

大学或机构: Johns Hopkins University(约翰•霍普金斯大学)

课程主页: https://www.coursera.org/course/ads1

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课程详情

DNA sequencing is now a ubiquitous tool in life science. You can observe this trend just by reading the news. This course examines the computational problems that come with this onslaught of DNA sequencing data. How do we take a huge collection of DNA "puzzle pieces" and assemble them into a genome? How do we make it quick and easy to find a DNA "needle" in an enormous genomic "haystack"? We will spend the bulk of the course understanding the algorithms and data structures that underlie software tools for analyzing sequencing data. The course is also an opporunity to practice programming skills and gain exposure to basic algorithms and data structures.

课程大纲

  • Sequencing
    • Introduction to DNA sequencing
    • Second-generation sequencing and parsing sequencing reads
  • Computational problems
    • Read alignment
    • De novo assembly
  • Exact matching
    • Strings
    • Exact matching problem and naive algorithm
    • Boyer-Moore
  • Preprocessing
    • Online versus offline algorithms
    • Indexing
    • Multimaps, binary search, hash tables
  • Approximate matching
    • Pigeonhole principle
    • Hamming and edit distance
    • Global and local alignment
  • De novo assembly
    • Overlaps
    • Shortest common superstring and greedy algorithm
    • De Bruijn graphs
    • How practical assemblers work

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课程简介

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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