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Bioinformatics

Pavel Pevzner, Phillip E. C. Compeau, Phillip Compeau, and Nikolay Vyahhi

Join Us in a Top 50 MOOC of All Time!

How do we sequence and compare genomes? How do we identify the genetic basis for disease? How do we construct an evolutionary Tree of Life for all species on Earth?

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Join Us in a Top 50 MOOC of All Time!

How do we sequence and compare genomes? How do we identify the genetic basis for disease? How do we construct an evolutionary Tree of Life for all species on Earth?

When you complete this Specialization, you will learn how to answer many questions in modern biology that have become inseparable from the computational approaches used to solve them. You will also obtain a toolkit of existing software resources built on these computational approaches and that are used by thousands of biologists every day in one of the fastest growing fields in science.

Although this Specialization centers on computational topics, you do not need to know how to program in order to complete it. If you are interested in programming, we feature an "Honors Track" (called "hacker track" in previous runs of the course). The Honors Track allows you to implement the bioinformatics algorithms that you will encounter along the way in dozens of automatically graded coding challenges. By completing the Honors Track, you will be a bioinformatics software professional!

Learn more about the Bioinformatics Specialization (including why we are wearing these crazy outfits) by watching our introductory video.

You can purchase the Specialization's print companion, Bioinformatics Algorithms: An Active Learning Approach, from the textbook website.

Our first course, "Finding Hidden Messages in DNA", was named a top-50 MOOC of all time by Class Central!

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What's inside

Seven courses

Finding Hidden Messages in DNA (Bioinformatics I)

(0 hours)
Named a top 50 MOOC of all time by Class Central! This course begins a series of classes illustrating the power of computing in modern biology. We will look for hidden messages in DNA without ever needing to put on a lab coat.
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Genome Sequencing (Bioinformatics II)

You may have heard about genome sequencing and its potential for personalized medicine. But what does it mean to sequence a genome? In this course, we will see how graph theory can be used to assemble genomes from short pieces of DNA. We will further learn about brute force algorithms and apply them to sequencing mini-proteins called antibiotics.
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Comparing Genes, Proteins, and Genomes (Bioinformatics III)

Once we have sequenced genomes, 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 or proteins. We will encounter dynamic programming to determine the number of mutations that have separated the two genes/proteins.
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Molecular Evolution (Bioinformatics IV)

In the previous course, we learned how to compare genes, proteins, and genomes. We can use these methods to construct a "Tree of Life" showing how organisms have evolved. In the first half, we will discuss approaches for evolutionary tree construction. In the second half, we will examine the claim that birds evolved from dinosaurs. Finally, you will learn how to apply bioinformatics software tools to reconstruct an evolutionary tree of ebolaviruses.
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Genomic Data Science and Clustering (Bioinformatics V)

How do we infer which genes orchestrate various processes in the cell? In this class, we will see that this question can be addressed using algorithmic and machine learning techniques arising from the general problem of dividing data points into distinct clusters.
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Finding Mutations in DNA and Proteins (Bioinformatics VI)

In previous courses, we discussed genome sequencing and comparison. This course covers advanced topics in finding mutations in DNA and proteins.
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Bioinformatics Capstone: Big Data in Biology

(0 hours)
In this course, you will learn how to use the BaseSpace cloud platform developed by Illumina to apply standard bioinformatics software approaches to real biological data. You will see how genome assembly can be used to track the source of a food poisoning outbreak, how RNA-Sequencing can help us analyze gene expression data on the tissue level, and compare the pros and cons of whole genome vs. whole exome sequencing for finding potentially harmful mutations in a human sample.
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Time
0 hours
Level
Introductory
Via
Coursera
Institution
University of California San Diego
Instructors
Pavel Pevzner
Phillip E. C. Compeau
Phillip Compeau
Nikolay Vyahhi
Level
Introductory
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