Back to Genome Sequencing (Bioinformatics II)
University of California San Diego

Genome Sequencing (Bioinformatics II)

You may have heard a lot about genome sequencing and its potential to usher in an era of personalized medicine, but what does it mean to sequence a genome? Biologists still cannot read the nucleotides of an entire genome as you would read a book from beginning to end. However, they can read short pieces of DNA. In this course, we will see how graph theory can be used to assemble genomes from these short pieces. We will further learn about brute force algorithms and apply them to sequencing mini-proteins called antibiotics. In the first half of the course, we will see that biologists cannot read the 3 billion nucleotides of a human genome as you would read a book from beginning to end. However, they can read shorter fragments of DNA. In this course, we will see how graph theory can be used to assemble genomes from these short pieces in what amounts to the largest jigsaw puzzle ever put together. In the second half of the course, we will discuss antibiotics, a topic of great relevance as antimicrobial-resistant bacteria like MRSA are on the rise. You know antibiotics as drugs, but on the molecular level they are short mini-proteins that have been engineered by bacteria to kill their enemies. Determining the sequence of amino acids making up one of these antibiotics is an important research problem, and one that is similar to that of sequencing a genome by assembling tiny fragments of DNA. We will see how brute force algorithms that try every possible solution are able to identify naturally occurring antibiotics so that they can be synthesized in a lab. Finally, you will learn how to apply popular bioinformatics software tools to sequence the genome of a deadly Staphylococcus bacterium that has acquired antibiotics resistance.

Status: Microbiology
Status: Bioinformatics
IntermediateCourse17 hours

Featured reviews

ZX

5.0Reviewed Jul 20, 2019

In depth and comprehensive coverage of the topics in genetic data analysis.

QL

5.0Reviewed Aug 27, 2017

It would be great if all the slides for every week could be shared. The Bioinformatics II is much harder than the last level. They've made it easy to learn.

CC

4.0Reviewed Jun 21, 2017

There is no debug dataset like the previous course, which means you will get stuck longer.

BN

4.0Reviewed Aug 5, 2020

Really enjoyed the course. Dropped from five to four stars because the final challenge introduced several new concepts rather than integrating concepts taught throughout the class.

DB

5.0Reviewed Jul 24, 2017

This is a well organized course with excellent interactive programming exercises that help with learning the concepts.

NS

5.0Reviewed Jul 23, 2017

I particularly enjoyed this course a lot more than the first! i felt it was more application oriented and intuitive.

FR

5.0Reviewed Apr 16, 2017

It's really a great course. A must for everyone working with bioinformatic tools in order to understand some basics and limitations that ultimately leads to biological conclussions

CG

4.0Reviewed Aug 6, 2020

Very good course. The course staff needs to take a look at some pseudo codes and stepik assessments because they are kinda heavy to process. Besides that, great info and development.

YL

5.0Reviewed Dec 26, 2016

Very helpful to those biologist who wants to start a career in bioinformatics

MZ

4.0Reviewed Sep 14, 2019

This course is great, but some times I can't open the dataset to test my code. I wish this can be fixed.

HN

5.0Reviewed Jun 8, 2017

These courses are consistently excellent. The are possiblly the best entry point for someone wishing to have a go at bioinformatics.

CF

5.0Reviewed Jul 14, 2021

The exercises were challenging. But thanks to the community in Stepik, I can understand more details for the genome sequencing algorithms.

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