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Comparing Genes, Proteins, and Genomes (Bioinformatics III)

Bioinformatics,

Once we have sequenced genomes in the previous course, we would like to compare them to determine how species have evolved and what makes them different. In the first half of the course, we will compare two short biological sequences, such as genes (i.e., short sequences of DNA) or proteins. We will encounter a powerful algorithmic tool called dynamic programming that will help us determine the number of mutations that have separated the two genes/proteins. In the second half of the course, we will "zoom out" to compare entire genomes, where we see large scale mutations called genome rearrangements, seismic events that have heaved around large blocks of DNA over millions of years of evolution. Looking at the human and mouse genomes, we will ask ourselves: just as earthquakes are much more likely to occur along fault lines, are there locations in our genome that are "fragile" and more susceptible to be broken as part of genome rearrangements? We will see how combinatorial algorithms will help us answer this question. Finally, you will learn how to apply popular bioinformatics software tools to solve problems in sequence alignment, including BLAST.

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Rating 4.7 based on 20 ratings
Length 7 weeks
Starts Aug 24 (5 weeks ago)
Cost $79
From University of California San Diego via Coursera
Instructors Pavel Pevzner, Phillip E. C. Compeau, Phillip Compeau, Nikolay Vyahhi
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Language English
Subjects Programming Science
Tags Computer Science Life Sciences Algorithms Bioinformatics Health Informatics

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What people are saying

behind genetics especially

for me this was a very intresting courde where I learined a lot about the research behind genetics especially how difficult it is to interprete the experiemntal data.

chromosme rearrangement analysis

A very well taught course that gives you the ins and outs of sequence comparision and introduces chromosme rearrangement analysis in a succint manner.

community building aspect

I also like the mathematical background in graph theory.Not being a boilogist I miss some extra inforamtion about the biological relevance and would like more pratical exemples before doing the final challenge which I found rather diffucult: only after reviewing my peers I really startd to onderstand the challenge.What I also miss is the community building aspect.

fully grasp what

Although this is a course in bioinformatics I often found myself laying on the bed with a piece of paper drawing graphs in order to fully grasp what I need to do so my code would be more efficient.Excellent work!

graph theory.not being

half an hour

So challenging, so rigorous, and so satisfying upon completion (which I just did half an hour ago).

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Rating 4.7 based on 20 ratings
Length 7 weeks
Starts Aug 24 (5 weeks ago)
Cost $79
From University of California San Diego via Coursera
Instructors Pavel Pevzner, Phillip E. C. Compeau, Phillip Compeau, Nikolay Vyahhi
Download Videos On all desktop and mobile devices
Language English
Subjects Programming Science
Tags Computer Science Life Sciences Algorithms Bioinformatics Health Informatics

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