Canada Spends Logo

Explore our Budget 2026 analysis

Grant: Team Grant: Canada-Japan CEEHRC Teams in Advancing Epigenetic Technologies

University of Manitoba

$298,500.00

Artificial Intelligence based adaptive and interpretable models for analyzing multi-track epigenomic sequential data

FY 2020-21

Summary
In this project we will take a fresh approach to harness the great potential of AI in the big data-analyses of epigenomic sequences. Epigenetics is the study of molecules and mechanisms that can perpetuate alternative gene activity states in the context of the same DNA sequence. Key factors in epigenetic control are chemical modifications to DNA and histones, which establish a complex regulatory network that controls genome function. Although epigenetic marks are established early during development and differentiation, adaptations occur throughout life in response to intrinsic (e.g. oncogenes) and environmental stimuli (e.g. diet) and may lead to disease late in life. Moreover, epigenomes react to environmental influence (e.g. maternal care, diet, exposure to toxins) with possibly long-term consequences. Thus, the life of an individual is not only defined by their genome, but also by their epigenome, which is flexible and changeable throughout the lifetime. The research team has two epigeneticists (Yamanaka, Davie) and two artificial intelligence (AI) experts (Ashraf, Khan). Working as a collaborative team, the four research groups will develop new tools to analyze DNA sequence data that will be able to predict 3D organization and functional aspects of these interactions in vertebrate epigenomes, which would be transformative in epigenetics research. We also propose the paradigm of iteratively refining the AI models through wet-experiments. In cancer, resistance to specific treatments often results in worse outcomes. It is now known that the 3D organization of the genome gets modified in these cancers. These sequence changes affect genome interactions and predispose some individuals to disease or an inadequate response to a virus attack as in COVID-19. Our studies have the potential to exploit the genome-wide data to predict the changes in the 3D organization of an individual's genome and gene activity, adding a new dimension to personalized medicine.
Program
Team Grant: Canada-Japan CEEHRC Teams in Advancing Epigenetic Technologies
Location
Manitoba, Canada
Recipient Type
Academia
Type
Grant
Source
CIHR Funding Decisions Database

As published

Id
437034
Name
Ashraf Ahmed
Region
Manitoba
Country
Canada
Orgtype
Institution Paid; Research Institution
Partnername
Japan Agency for Medical Research and Development
Instname2
Genetics
Theme2
Biomedical
Prcname2
Special Cases
Projecttitle
Artificial Intelligence based adaptive and interpretable models for analyzing multi-track epigenomic sequential data
Programtype2
Operating Grants
Orgnameinp2
University of Manitoba
Cihramount2
$298,500
Cihrequipment2
$0
Programname2
Team Grant: Canada-Japan CEEHRC Teams in Advancing Epigenetic Technologies
Keyworddelim
3d Chromatin; 3d Genome; Artificial Intelligence; Deep Learning; Epigenetics; Machine Learning; Sequence Modeling
Abstract
In this project we will take a fresh approach to harness the great potential of AI in the big data-analyses of epigenomic sequences. Epigenetics is the study of molecules and mechanisms that can perpetuate alternative gene activity states in the context of the same DNA sequence. Key factors in epigenetic control are chemical modifications to DNA and histones, which establish a complex regulatory network that controls genome function. Although epigenetic marks are established early during development and differentiation, adaptations occur throughout life in response to intrinsic (e.g. oncogenes) and environmental stimuli (e.g. diet) and may lead to disease late in life. Moreover, epigenomes react to environmental influence (e.g. maternal care, diet, exposure to toxins) with possibly long-term consequences. Thus, the life of an individual is not only defined by their genome, but also by their epigenome, which is flexible and changeable throughout the lifetime. The research team has two epigeneticists (Yamanaka, Davie) and two artificial intelligence (AI) experts (Ashraf, Khan). Working as a collaborative team, the four research groups will develop new tools to analyze DNA sequence data that will be able to predict 3D organization and functional aspects of these interactions in vertebrate epigenomes, which would be transformative in epigenetics research. We also propose the paradigm of iteratively refining the AI models through wet-experiments. In cancer, resistance to specific treatments often results in worse outcomes. It is now known that the 3D organization of the genome gets modified in these cancers. These sequence changes affect genome interactions and predispose some individuals to disease or an inadequate response to a virus attack as in COVID-19. Our studies have the potential to exploit the genome-wide data to predict the changes in the 3D organization of an individual's genome and gene activity, adding a new dimension to personalized medicine.
Competitiondate
202010
Approvedterm2
3 yrs 0 mth
Pinamesdelim
Ashraf, Ahmed
Approvedterm
3 ans 0 mois
Cihrcontribution2
Inst of Cancer Research~ $17,931~ $0~Inst of Neurosc Mental Hlth &A~ $17,931~ $0~Institute of Genetics~ $17,930~ $0~Major Initiatives #3~ $244,708~ $0~
University of Manitoba - $298,500 Grant (2020-21) | Canada Spends