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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Universidad Johns HopkinsAcerca de este Curso
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Subtítulos: Árabe (Arabic), Francés (French), Portugués (europeo), Italiano, Vietnamita, Alemán (German), Ruso (Russian), Inglés (English), Español (Spanish)
Habilidades que obtendrás
- Bioinformatics Algorithms
- Algorithms
- Python Programming
- Algorithms On Strings
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Aprox. 12 horas para completar
Inglés (English)
Subtítulos: Árabe (Arabic), Francés (French), Portugués (europeo), Italiano, Vietnamita, Alemán (German), Ruso (Russian), Inglés (English), Español (Spanish)
ofrecido por
Universidad Johns Hopkins
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.
Programa - Qué aprenderás en este curso
4 horas para completar
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.
4 horas para completar
19 videos (Total 112 minutos), 7 lecturas, 2 cuestionarios
3 horas para completar
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
3 horas para completar
15 videos (Total 114 minutos), 1 lectura, 2 cuestionarios
3 horas para completar
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.
3 horas para completar
13 videos (Total 92 minutos), 1 lectura, 2 cuestionarios
3 horas para completar
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.
3 horas para completar
13 videos (Total 83 minutos), 1 lectura, 2 cuestionarios
Reseñas
- 5 stars80,75 %
- 4 stars14,87 %
- 3 stars3 %
- 2 stars0,50 %
- 1 star0,87 %
Principales reseñas sobre ALGORITHMS FOR DNA SEQUENCING
por KP18 de may. de 2020
Very good course this is. Just a little advice, please make the quiz questions more clear and more specific because one shouldn't waste time to understand a question which is very easy to implement.
por SS3 de jul. de 2018
Very well prepared, from basics up to all commonly used techniques in bioinformatics. Prerequisites in Python is a plus, but not even necessary.
por NF9 de mar. de 2021
very engaging and well-presented course material.
intermediate difficulty while conveying the basics of how even recent real-world genome alignment and assembly tools work. great course design!
por MD9 de nov. de 2016
This was really fun. Really enjoyed the a-ha of the algorithms and the fun of solving the alignment and assembly problems. Feel mildly powerful after assembling a virus genome.
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