Bioinformatics Algorithms (Part 1)
Pavel Pevzner and Phillip E. C. Compeau
This course will cover some of the common algorithms underlying the following fundamental topics in bioinformatics: assembling genomes, comparing DNA and protein sequences, predicting genes, finding regulatory motifs, analyzing gene expression, constructing evolutionary trees, analyzing genome rearrangements, and identifying proteins.
Next Session:
| Date to be announced (6 weeks long) | Sign Up |
Workload: 8-10 hours/week
About the Course
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.
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.
Course Syllabus
Note: the syllabus may undergo revisions throughout the course. While no textbook is required for this course, you may find the following textbook useful:J&P – Jones and Pevzner, An Introduction to Bioinformatics Algorithms (The MIT Press)
Each homework will consist of 5 programming assignments and will utilize the Rosalind bioinformatics online education platform: http://rosalind.info
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