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SUMMARY:Does a giraffe need a telomere-to-telomere diploid genome assembly
 ?
DTSTART;TZID=Europe/London:20260903T100000
DTEND;TZID=Europe/London:20260903T110000
DTSTAMP:20260626T203436Z
UID:4fcdcc3d-c964-f111-ab0d-7ced8d9a5614
CREATED:20260610T123816Z
DESCRIPTION:For our BDI Distinguished Seminar\, we will hear from Professo
 r Pavel Pevzner\, Ronald R. Taylor Chair and Distinguished Professor of Co
 mputer Science and Engineering at the University of California\, San Diego
 \, on Thursday 3 September\, 10:00 am – 11:00 am\, at the Big Data Insti
 tute (BDI). \n\nTitle: Does a giraffe need a telomere-to-telomere diploid 
 genome assembly? \n\nDate: Thursday 3 September\nTime: 10:00 am - 11:00 am
 \nVenue: BDI/OxPop\, Seminar Room 0\; followed by refreshments in the atri
 um\n\nAbstract:\nRecent telomere-to-telomere (T2T) sequencing projects hav
 e transformed genomics by delivering near-complete diploid assemblies that
  reconstruct both haplomes. However\, attaining this gold standard remains
  labor-intensive\, requiring multiple sequencing technologies\, manual cur
 ation\, and a level of dedication that occasionally borders on obsession. 
 \nFortunately\, biologists often do not need a gold-plated diploid genome 
 to study their favorite species. For many applications\, a near-complete h
 aplotype-mixed (HM) assembly—a “virtual child” genome representing a
  mosaic of the two haplomes—captures most of the information required fo
 r downstream analyses while avoiding much of the cost and complexity of di
 ploid assembly. In principle\, HM assemblies can be generated automaticall
 y and inexpensively using a single sequencing technology (e.g.\, long and 
 accurate HiFi or ONT reads). In practice\, however\, existing HM assembler
 s still struggle to generate near-complete assemblies.\nWe present the Mos
 aic Genome Assembler (MGA)\, which constructs near-complete HM assemblies 
 from a single sequencing technology. Benchmarking across diverse genomes s
 hows that MGA substantially outperforms existing haplotype-mixed assembler
 s while eliminating the need for additional sequencing technologies. MGA d
 oes not replace T2T diploid assemblies\; rather\, it offers a pragmatic al
 ternative for the many projects that need a high-quality “virtual child
 ” reference genome\, but not necessarily Mom and Dad genomes.\nAbout the
  speaker:\nPavel Pevzner is the Ronald R. Taylor Chair and Distinguished P
 rofessor of Computer Science and Engineering at the University of Californ
 ia\, San Diego. He received his Ph.D. from Moscow Institute of Physics and
  Technology\, Russia. Dr. Pevzner was named a Howard Hughes Medical Instit
 ute Professor in 2006 and has received various accolades\, including elect
 ion as a Fellow of the Association for Computing Machinery (2010)\, the In
 ternational Society for Computational Biology (2012)\, the Academia Europa
 ea (2016)\, and the American Association for the Advancement of Science (2
 018). He has received honorary doctorates from Simon Fraser University (20
 11) and Tel Aviv University (2023)\, the Senior Scientist Award from the I
 nternational Society for Computational Biology (2017)\, and the Kanellakis
  Theory and Practice Award from the Association for Computing Machinery (2
 019). Dr. Pevzner authored textbooks "Computational Molecular Biology: An 
 Algorithmic Approach"\, "Introduction to Bioinformatics Algorithms" (with 
 Neal Jones)\, “Bioinformatics Algorithms: an Active Learning Approach”
  (with Phillip Compeau)\, and “Learning Algorithms through Programming a
 nd Puzzle Solving” (with Alexander Kulikov). He also co-developed the Co
 ursera online specializations in Bioinformatics and Algorithms\, which hav
 e collectively attracted over 700\,000 learners worldwide.
LAST-MODIFIED:20260622T104541Z
LOCATION:Big Data Institute - Lower Ground Seminar Room 0\, Lower Ground S
 eminar Room 0 Big Data Institute Old Road Campus Oxford Oxfordshire OX3 7L
 F United Kingdom
SPEAKER:Prof Pavel Pevzner (University of California at San Diego (UCSD))
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