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.
More info: http://cseweb.ucsd.edu/~ppevzner/

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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 [...]

Hacking COVID-19 — Course 3: Unraveling COVID-19's Origins (Coursera)

In this course, you will follow in the footsteps of the bioinformaticians investigating the COVID-19 outbreak by investigating the origins of SARS-CoV-2. Whether you’re new to the world of computational biology, or you’re a bioinformatics expert seeking to learn about its applications in the COVID-19 pandemic, or somewhere in [...]

Hacking COVID-19 — Course 2: Decoding SARS-CoV-2's Secrets (Coursera)

In this course, you will follow in the footsteps of the bioinformaticians investigating the COVID-19 outbreak by annotating the SARS-CoV-2 genome and using the annotation to design a COVID-19 diagnostic test. Whether you’re new to the world of computational biology, or you’re a bioinformatics expert seeking to learn about [...]

Hacking COVID-19 — Course 1: Identifying a Deadly Pathogen (Coursera)

In this course, you will follow in the footsteps of the bioinformaticians investigating the COVID-19 outbreak by assembling the SARS-CoV-2 genome. Whether you’re new to the world of computational biology, or you’re a bioinformatics expert seeking to learn about its applications in the COVID-19 pandemic, or somewhere in between, [...]

Algorithms and Data Structures Capstone (edX)

Synthesize your knowledge of algorithms and biology to build your own software for solving a biological challenge. Building a fully-fledged algorithm to assemble genomes from DNA fragments on a real dataset is an enormous challenge with major demand in the multi-billion dollar biotech industry. In this capstone project, we [...]

Dynamic Programming: Applications In Machine Learning and Genomics (edX)

Learn how dynamic programming and Hidden Markov Models can be used to compare genetic strings and uncover evolution. If you look at two genes that serve the same purpose in two different species, how can you rigorously compare these genes in order to see how they have evolved away [...]

String Processing and Pattern Matching Algorithms (edX)

Learn about pattern matching and string processing algorithms and how they apply to interesting applications. The world and internet are full of textual information. We search for information using textual queries and read websites, books and e-mails.