Pavel Pevzner

Pavel Pevzner is Professor of Computer Science and Engineering at University of California San Diego (UCSD), where he holds the Ronald R. Taylor Chair and has taught a Bioinformatics Algorithms course for the last 12 years. His research concerns the creation of bioinformatics algorithms for analyzing genome rearrangements, DNA sequencing, and computational proteomics.
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Biology Meets Programming: Bioinformatics for Beginners (Coursera)

Are you interested in learning how to program (in Python) within a scientific setting? This course will cover algorithms for solving various biological problems along with a handful of programming challenges helping you implement these algorithms in Python.
Average: 1 ( 3 votes )

Algorithmic Toolbox (Coursera)

The course covers basic algorithmic techniques and ideas for computational problems arising frequently in practical applications: sorting and searching, divide and conquer, greedy algorithms, dynamic programming. We will learn a lot of theory: how to sort data and how it helps for searching; how to break a large problem [...]
Average: 7 ( 3 votes )

Finding Mutations in DNA and Proteins (Bioinformatics VI) (Coursera)

In previous courses in the Specialization, we have discussed how to sequence and compare genomes. This course will cover advanced topics in finding mutations lurking within DNA and proteins. In the first half of the course, we would like to ask how an individual's genome differs from the "reference [...]
Average: 7 ( 4 votes )

Molecular Evolution (Bioinformatics IV) (Cousera)

In the previous course in the Specialization, we learned how to compare genes, proteins, and genomes. One way we can use these methods is in order to construct a "Tree of Life" showing how a large collection of related organisms have evolved over time.
Average: 5 ( 3 votes )

Comparing Genes, Proteins, and Genomes (Bioinformatics III) (Coursera)

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 [...]
Average: 10 ( 4 votes )

Genome Sequencing (Bioinformatics II) (Coursera)

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. [...]
Average: 4 ( 4 votes )

Finding Hidden Messages in DNA (Bioinformatics I) (Coursera)

This course begins a series of classes illustrating the power of computing in modern biology. Please join us on the frontier of bioinformatics to look for hidden messages in DNA without ever needing to put on a lab coat. In the first half of the course, we investigate DNA [...]
Average: 6 ( 3 votes )

Algorithms on Strings (Coursera)

World and internet is full of textual information. We search for information using textual queries, we read websites, books, e-mails. All those are strings from the point of view of computer science. To make sense of all that information and make search efficient, search engines use many string algorithms. [...]
Average: 8 ( 3 votes )

Genome Assembly Programming Challenge (Coursera)

In Spring 2011, thousands of people in Germany were hospitalized with a deadly disease that started as food poisoning with bloody diarrhea and often led to kidney failure. It was the beginning of the deadliest outbreak in recent history, caused by a mysterious bacterial strain that we will refer [...]
Average: 3 ( 4 votes )

Genomic Data Science and Clustering (Bioinformatics V) (Coursera)

How do we infer which genes orchestrate various processes in the cell? How did humans migrate out of Africa and spread around the world? In this class, we will see that these two seemingly different questions can be addressed using similar algorithmic and machine learning techniques arising from the [...]
Average: 5 ( 3 votes )