Lila Kari and M. Tamer Özsu lend CS expertise to BIOSCAN, a global multidisciplinary biodiversity project

Wednesday, January 12, 2022

The biosphere, the zone in which life on Earth is found, contains an estimated 10 million multicellular species. But perhaps the most surprising fact about life on Earth is how little we know about its diversity. Only 2 million species are known to science — organisms that have been studied in sufficient detail to at least be described, classified and given a scientific name. With at least another 8 million species yet to be discovered, cataloguing the diversity of life is in many ways a moonshot — a vast endeavour that succeeds by bringing together specialists across many disciplines.

The bewildering diversity of life on Earth has meant that developing a system to catalogue species has been painstakingly slow. Traditionally, species discovery and taxonomy has been the purview of field biologists who laboriously observe, collect and classify organisms across the planet’s frigid poles to its temperate and tropical zones. In recent years, however, the power of DNA sequencing coupled with the ability to identify species using only short stretches of their DNA has transformed the field of biodiversity. 

This revolution — a DNA barcoding system that uses a small DNA fragment to discriminate species — not only promises to complete the catalogue of life, but it will generate important insights into the age of species and their relationships. Known as BIOSCAN, this multinational, multidisciplinary project to complete the inventory of species, reveal their interactions, and assess their response to ecosystem change is led by Professor Paul Hebert, an evolutionary biologist at the University of Guelph who holds the Tier 1 Canada Research Chair in Molecular Biodiversity

Professor Hebert and his international team of co-principal investigators and co-applicants have just received $24 million from Canada’s New Frontiers in Research Fund to expand the scope of the BIOSCAN project, the largest research program ever undertaken in biodiversity science.

Among the dozens of researchers on this ambitious project are Cheriton School of Computer Science Professors Lila Kari and M. Tamer Özsu

photo of Professor Lila Kari and M. Tamer Özsu

L to R: Professors Lila Kari and M. Tamer Özsu

Lila Kari, Professor and University Research Chair at the Cheriton School of Computer Science, is author of more than 200 peer-reviewed articles. She is one of the world’s experts in biomolecular computation — using biological, chemical and other natural systems to perform computations.

M. Tamer Özsu, a University Professor at the Cheriton School of Computer Science, is a Fellow of the Royal Society of Canada, a Fellow of the American Association for the Advancement of Science, a Fellow of the Association for Computing Machinery, and a Fellow of the Institute of Electrical and Electronics Engineers. His research centres on large-scale data distribution and management of non-relational data.

Professor Kari, a co-applicant on the BIOSCAN project, brings her expertise in biodiversity informatics and AI to develop efficient machine learning algorithms that extract compositional information from both structured and unstructured genomic data, towards BIOSCAN’s main goal and other underlying applications.

As a co-principal investigator, University Professor Özsu brings his expertise in data science to the informatics team that will develop the next-generation data management tools to manage the large and varied data BIOSCAN will collect as well as data engineering tools and methodologies to prepare the data for analysis and exploration.

  1. 2022 (4)
    1. January (4)
  2. 2021 (64)
    1. December (2)
    2. November (6)
    3. October (6)
    4. September (4)
    5. August (7)
    6. July (4)
    7. June (8)
    8. May (9)
    9. April (3)
    10. March (8)
    11. February (4)
    12. January (3)
  3. 2020 (73)
    1. December (7)
    2. November (6)
    3. October (4)
    4. September (5)
    5. August (4)
    6. July (7)
    7. June (4)
    8. May (11)
    9. April (13)
    10. March (3)
    11. February (3)
    12. January (6)
  4. 2019 (90)
  5. 2018 (82)
  6. 2017 (50)
  7. 2016 (27)
  8. 2015 (41)
  9. 2014 (32)
  10. 2013 (46)
  11. 2012 (17)
  12. 2011 (20)