Project 457575
Multiomic & Biomechanical Characterization of Aortopathy using Machine Learning Approach: Towards Personalized Prognostication & Surgical Thresholds
457575
Multiomic & Biomechanical Characterization of Aortopathy using Machine Learning Approach: Towards Personalized Prognostication & Surgical Thresholds
$150,000
Project Information
| Study Type: | Unclear |
| Research Theme: | Biomedical |
Institution & Funding
| Principal Investigator(s): | Elbatarny, Malak |
| Institution: | University of Toronto |
| CIHR Institute: | Genetics |
| Program: | |
| Peer Review Committee: | Vanier Canada Graduate Scholarships CIHR |
| Competition Year: | 2021 |
| Term: | 3 yrs 0 mth |
Abstract Summary
Aortic dilation can be deadly and often needs surgery, but is unpredictable. We will derive computer-generated comparisons between gene sequences, gene activity level, proteins, and strength of dilated and normal aortic tissues to identify predictors of worsening aortic dilation.
No special research characteristics identified
This project does not include any of the advanced research characteristics tracked in our database.
Keywords
Bioinformatics
Biomechanics
Cardiac Surgery
Genomics
Proteomics
Thoracic Aneurysm
Transcriptomics