Grant: Alliance Grants
Toronto Metropolitan University
$25,000.00
Non-coding RNA Structure Analysis Based on Deep Neural Networks
EF 2022-23
Résumé
The main objective of this collaboration is to develop new machine learning algorithms to analyze non-coding ribonucleic acid (ncRNA) structures based on recent developments in deep neural networks. ncRNAs play important roles in cell processes such as to effect high-order chromosomal dynamics, telomere biology, subcellular structural organization, and gene expression. Analyzing ncRNA structure is a fundamental step towards understanding their biological functions. Through this collaboration with the University of Kansas, this project addresses a very important interdisciplinary problem that involves ncRNA, computational biology, and machine learning. It will provide a new bioinformatics infrastructure for sequencing data analysis which will have significant research impacts in biomedicine, biology, RNA therapeutics, and drug discovery, while promoting Canada's global leadership in bioengineering and artificial intelligence.
Programme
Alliance Grants
Bénéficiaire
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
576612-2022
Name nom
Wang, Guanghui G
Department département
Computer Science
Organization id
43
Institution établissement
Toronto Metropolitan University
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2022
Competition year année de concours
2022
Award amount
25000
Program id
ALLRP
Program name en
Alliance Grants
Program name fr
Subventions Alliance
Group en
RESEARCH PARTNERSHIPS
Group fr
PARTENARIATS DE RECHERCHE
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
9999
Area of application group en
Not available
Area of application group fr
Non disponible
Area of application en
Not available
Area of application fr
Non disponible
Research subject code
2800
Research subject group en
Artificial intelligence
Research subject group fr
Intelligence artificielle
Research subject en
Artificial intelligence (computer vision, use2603)
Research subject fr
Intelligence artificielle (vision artificielle, utiliser 2603)
Installment
inst:1
Partie
1
Nb partie
1
Application title
Non-coding RNA Structure Analysis Based on Deep Neural Networks
Application summary
The main objective of this collaboration is to develop new machine learning algorithms to analyze non-coding ribonucleic acid (ncRNA) structures based on recent developments in deep neural networks. ncRNAs play important roles in cell processes such as to effect high-order chromosomal dynamics, telomere biology, subcellular structural organization, and gene expression. Analyzing ncRNA structure is a fundamental step towards understanding their biological functions. Through this collaboration with the University of Kansas, this project addresses a very important interdisciplinary problem that involves ncRNA, computational biology, and machine learning. It will provide a new bioinformatics infrastructure for sequencing data analysis which will have significant research impacts in biomedicine, biology, RNA therapeutics, and drug discovery, while promoting Canada's global leadership in bioengineering and artificial intelligence.
