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Курс от Johns Hopkins University
courseraАнализ данных
Algorithms for DNA Sequencing
Курс от Johns Hopkins UniversityО курсе
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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Программа курса
4 модулей · 78 учебных материалов
01DNA sequencing, strings and matching28 материалов
02Preprocessing, indexing and approximate matching18 материалов
Module 2: Preprocessing, indexing and approximate matching
Week 2 Introduction ВидеоLecture: Boyer-Moore basicsВидеоLecture: Boyer-Moore: putting it all togetherВидеоLecture: Diversion: Repetitive elementsВидеоPractical: Implementing Boyer-Moore Видео03Edit distance, assembly, overlaps16 материалов
Module 3: Edit distance, assembly, overlaps
Module 3 Introduction ВидеоLecture: Solving the edit distance problemВидеоLecture: Using dynamic programming for edit distanceВидеоPractical: Implementing dynamic programming for edit distance ВидеоLecture: A new solution to approximate matchingВидеоLecture: Meet the family: global and local alignment04Algorithms for assembly16 материалов
Module 4: Algorithms for assembly
Module 4 introduction ВидеоLecture: The shortest common superstring problemВидеоPractical: Implementing shortest common superstring ВидеоLecture: Greedy shortest common superstringВидеоPractical: Implementing greedy shortest common superstring ВидеоLecture: Third law of assembly: repeats are badУчитесь у экспертов
Ben Langmead, PhD
Assistant Professor
Jacob Pritt
Преподаватель курса