Bioinformatics Algorithms (Part 1)
开始时间: 04/22/2022
持续时间: Unknown
课程主页: https://www.coursera.org/course/bioinformatics
课程评论: 2 个评论
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课程详情
Sequencing the human genome in 2001 started a computational revolution
in biology, which has arguably been an impetus for more new algorithms
than any other fundamental realm of science. The newly formed links
between computer science and biology affect the way we teach computational
ideas to biologists, as well as how applied algorithms are taught to computer
scientists.
Genome sequencing is just one of hundreds of biological problems that
have become inextricable from the computational methods required to solve
them. In this course, we will take a look at some of the algorithmic ideas
that are fundamental to an understanding of modern biology.
Computational concepts like dynamic programming and network analysis will
help us explore algorithms applied to a wide range of biological topics,
from finding genes to reconstructing the tree of life. Throughout
the process, we will apply real bioinformatics tools and analyze real genetic
data.
In order to streamline homework assignments and solidify the material
covered in the course, we will employ Rosalind (http://rosalind.info),
a fun new resource for learning bioinformatics that was founded by
the instructors. We hope that Rosalind will show you how
fun solving problems in bioinformatics can be.
课程大纲
Note: the syllabus may undergo revisions throughout the course.
Each homework will consist of approximately 5 programming assignments
and will utilize the Rosalind bioinformatics online education platform:
http://rosalind.info
Week 1
Topics
- Introduction
- Algorithms Primer
- Molecular Biology
Primer
- The Motif Finding
Problem
- Genome
Rearrangements
Homework
- Programming Assignment
#1: Computing rearrangement distance between genomes/Finding regulatory
motifs
Week 2
Topics
- Edit Distance
- Pairwise Sequence
Alignment
- Multiple Sequence
Alignment
Homework
- Programming
Assignment #2: Constructing Optimal Overlap Alignment/Constructing Chimeric
Alignments
Week 3
Topics
- Gene Prediction and
Spliced Alignment
- Space-Efficient
Sequence Alignment
- Applications of Suffix
Trees and Suffix Arrays in Bioinformatics
- BLAST
Homework
- Programming
Assignment #3: Exon
Chaining Problem/Finding Longest Repeats
Week 4
Topics
- DNA Sequencing
- Burrows Wheeler
Transform (BWA) for Read Mapping in DNA Sequencing
Homework
- Programming Assignment
#4: Constructing de Bruijn graphs and Fragment Assembly
Week 5
Topics
- Peptide Sequencing and
Protein Identification
- Spectral Alignment
- Gibbs Sampling and
Random Projections for Motif Finding
Homework
- Programming Assignment
#5: Antisymmetric Path Problem for de novo Peptide Sequencing/Finding
Motifs using Gibbs Sampling
Week 6
Topics
- DNA Arrays and
Clustering Algorithms
- Distance-Based
Algorithms for Evolutionary Tree
Reconstruction
- Character-Based
Algorithms for Evolutionary Tree
Reconstruction
- Profile Hidden Markov
Models for Sequence Alignment
Homework
- Programming
Assignment #6: Solving Small Parsimony Problems/Finding a Hidden Path in
a Profile HMM
课程评论(2条)
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曹单锋
2014-01-28 14:38
1 票支持; 0 票反对
导师是生物信息算法领域无人不知的大牛。课程涉及很多算法，贪心、图论、动态规划等等。课程有点难，需要一定的编程能力，论坛里经常有人发“I’m out”之类的帖子。总共10周的课程，作业都是编程题，每周都会有4-8个，总共64题，通过60%给证，通过80%优秀。我每周都花>15h的时间在这门课上，中途也有放弃的念头，后面几周的作业很多没写，最后60+飘过。统计了下，我一共写了4000+行的代码(C++)。。。收获非常大，寒假打算再复习一遍。几个月之后还会有part2，我肯定也是会修的。
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xtliwen
2013-05-31 15:38
0 票支持; 0 票反对
作为生物专业的我，非常期待生物信息学的课程。在考研究生的时候，考得就是生物信息学专业，只可惜导师收满了学生，和生物信息学插肩而过。看了课程信息，非常实用，希望能够重拾当时的热情。
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