Grant: Alliance Grants
Université d'Ottawa
$30,000.00
Decoding molecular signatures in solid-state nanopore signals using AI/ML
FY 2023-24
Summary
This project will advance solid-state nanopore signal processing and analysis capabilities toward automated denoising and characterization of nanopore signals using AI/ML approaches. It is a critical part of the roadmap to enabling downstream healthcare applications of solid-state nanopores via single-molecule proteomics. Scientific instrumentation for life sciences is undergoing a revolution. New technologies are emerging that can detect individual molecules to enable important new opportunities in biotechnology and healthcare. Nanopores are molecular-sized holes in thin membranes that enable purely electrical sensing for single molecule detection. A core part of realizing the potential of this technology to disrupt healthcare is the development of analysis that automate complex related signal processing tasks. The University of Ottawa previously developed a key technology that overcomes one of the challenges to realizing solid-state nanopore potential: the controlled breakdown method, which automates fabrication of individual nanopores down to 1-nm in size with unmatched precision. This innovation has already been productized by our partner, Northern Nanopore Instruments. This project aims to build on recent advances in AI/ML approaches to data processing to address one of the other challenges: automating complex signal processing tasks that currently represent a barrier to rapid progress. In the course of this work, we will develop novel methods to denoise and fit nanopore signals, as well as use the latest advances in generative AI to augment the quality and quantity of data available, tools which will also be commercialized as part of Northern Nanopore's enabling solid-state nanopore research platform. Ultimately, this project will help Canada strengthen its position as a global leader in the development of new health and nanotechnologies.
Program
Alliance Grants
Recipient
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
586371-2023
Name nom
Harden, James J
Department département
Physics
Organization id
28
Institution établissement
Université d'Ottawa
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2023
Competition year année de concours
2023
Award amount
30000
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
1201
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Life sciences (including biotechnology)
Area of application fr
Sciences de la vie (y compris biotechnologie)
Research subject code
1901
Research subject group en
Biomedical engineering
Research subject group fr
Biomedical technology
Research subject en
Génie biomédical
Research subject fr
Technologie biomédicale
Application title
Decoding molecular signatures in solid-state nanopore signals using AI/ML
Keyword
artificial intelligence; convolutional neural networks; digital signal process; generative adversarial networks; machine learning; personalized medicine; proteomics; recurrent neural networks; solid-state nanopore; statistical analysis
Application summary
This project will advance solid-state nanopore signal processing and analysis capabilities toward automated denoising and characterization of nanopore signals using AI/ML approaches. It is a critical part of the roadmap to enabling downstream healthcare applications of solid-state nanopores via single-molecule proteomics. Scientific instrumentation for life sciences is undergoing a revolution. New technologies are emerging that can detect individual molecules to enable important new opportunities in biotechnology and healthcare. Nanopores are molecular-sized holes in thin membranes that enable purely electrical sensing for single molecule detection. A core part of realizing the potential of this technology to disrupt healthcare is the development of analysis that automate complex related signal processing tasks. The University of Ottawa previously developed a key technology that overcomes one of the challenges to realizing solid-state nanopore potential: the controlled breakdown method, which automates fabrication of individual nanopores down to 1-nm in size with unmatched precision. This innovation has already been productized by our partner, Northern Nanopore Instruments. This project aims to build on recent advances in AI/ML approaches to data processing to address one of the other challenges: automating complex signal processing tasks that currently represent a barrier to rapid progress. In the course of this work, we will develop novel methods to denoise and fit nanopore signals, as well as use the latest advances in generative AI to augment the quality and quantity of data available, tools which will also be commercialized as part of Northern Nanopore's enabling solid-state nanopore research platform. Ultimately, this project will help Canada strengthen its position as a global leader in the development of new health and nanotechnologies.