Dr. Pavel Pevzner from University of California, San Diego presents a lecture titled "Algorithms & Optimization."

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https://drive.google.com/open?id=0B4I...

Lecture Abstract
This lecture will illustrate algorithmic challenges in Biological Data Science using genome assembly. We will show how modern algorithms solve the seemingly intractable problem of assembling a jigsaw puzzle with billions of short pieces (sequencing reads). We will discuss how the best algorithmic strategies for assembling genomes from reads change as new sequencing technologies emerge. The factors that influence the choice of algorithms include the quantity of data (measured by read length and coverage); quality of data (including error rates); and genome structure (the number and size of repeated regions).


About the Speaker
Pavel Pevzner is Ronald R. Taylor Professor of Computer Science and Engineering and Director of the NIH National Center for Computational Mass Spectrometry at University of California, San Diego. He holds Ph.D. from Moscow Institute of Physics and Technology, Russia. He was named Howard Hughes Medical Institute Professor in 2006. He was elected the ACM Fellow (2010) for "contribution to algorithms for genome rearrangements, DNA sequencing, and proteomics”, International Society for Computational Biology Fellow (2012), and European Academy of Sciences (Academia Europaea) in 2016. He was awarded a Honoris Causa (2011) from Simon Fraser University in Vancouver. Dr. Pevzner authored textbooks "Computational Molecular Biology: An Algorithmic Approach", "Introduction to Bioinformatics Algorithms" (jointly with Neal Jones) and “Bioinformatics Algorithms: an Active Learning Approach” (jointly with Phillip Compeau). In 2015, jointly with Phillip Compeau, he developed a Bioinformatics specialization on Coursera (a series of 7 courses) that has already have over 300,000 enrollments. In 2016, Compeau and Pevzner developed Biology Meets Programming online course on Coursera that introduces biologists to programming.


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