Title:
Assembly of Big Genomic Data

dc.contributor.author Medvedev, Paul
dc.contributor.corporatename Georgia Institute of Technology. Institute for Data Engineering and Science en_US
dc.contributor.corporatename Pennsylvania State University en_US
dc.date.accessioned 2017-10-02T16:13:25Z
dc.date.available 2017-10-02T16:13:25Z
dc.date.issued 2017-09-15
dc.description Presented on September 15, 2017 from 2:00 p.m.-3:00 p.m. in the Technology Square Research Building (TSRB) Auditorium, Georgia Tech. en_US
dc.description IDEaS Seminar Series en_US
dc.description Paul Medvedev is an Assistant Professor at the Pennsylvania State University in the departments of "Computer Science and Engineering" and "Biochemistry and Molecular Biology." Prior to joining Penn State, he was a postdoc with Pavel Pevzner in UC San Diego and received his Ph.D. at the University of Toronto in Computer Science under the supervision of Michael Brudno and Allan Borodin. en_US
dc.description Runtime: 57:58 minutes
dc.description.abstract As genome sequencing technologies continue to facilitate the generation of large datasets, developing scalable algorithms has come to the forefront as a crucial step in analyzing these datasets. In this talk, I will discuss several recent advances, with a focus on the problem of reconstructing a genome from a set of reads (genome assembly). I will describe low-memory and scalable algorithms for automatic parameter selection and de Bruijn graph compaction, recently implemented in two tools: KmerGenie and bcalm. I will also present recent advances in the theoretical foundations of genome assemblers. en_US
dc.format.extent 57:58 minutes
dc.identifier.uri http://hdl.handle.net/1853/58814
dc.language.iso en_US en_US
dc.publisher Georgia Institute of Technology en_US
dc.relation.ispartofseries IDEaS Seminar Series en_US
dc.subject Big data en_US
dc.subject Bioinformatics en_US
dc.subject Genome assembly en_US
dc.title Assembly of Big Genomic Data en_US
dc.type Moving Image
dc.type.genre Lecture
dspace.entity.type Publication
local.contributor.corporatename Institute for Data Engineering and Science
local.relation.ispartofseries IDEaS Seminar Series
relation.isOrgUnitOfPublication 2c237926-6861-4bfb-95dd-03ba605f1f3b
relation.isSeriesOfPublication 315185f2-d0ec-4ea2-8fdc-822ed04da3a8
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