Deep learning tools for tissue-specific disease risk prediction

Supervisors

Mafalda Dias and Jonathan Frazer
CRG, 1st supervisors

Objectives

Comparing protein sequences across species has long been a powerful approach for identifying critical amino acids that influence protein function and disease risk. Recent advances in deep generative models allow us to model complex patterns of genetic constraint, offering new tools for disease risk prediction and diagnosis. This project aims to leverage the vast diversity of life to model genetic constraints on sequences and gene expression in specific tissues, ultimately advancing our understanding of the molecular basis of age-associated disease.

Methodology

– Develop deep generative models to analyse patterns of genetic constraint in protein sequences across diverse species.
– Model constraints on gene expression in specific tissues to identify biomarkers of a healthy state.
– Build predictive tools for assessing tissue-specific disease risk based on genetic variation.

Required Skills

We are looking for a student with a computational biology, computer science, physics or mathematics background. Comfort with coding and model building are a requirement. Comfort with deep learning or gene expression data is preferable but not required. And most importantly, we are looking for someone curious, inquisitive and scientifically generous to join our joyful team of scientists.

Expected Results

The project will produce advanced deep learning models capable of predicting tissue-specific disease risks by analysing genetic constraints. These tools will enhance disease risk prediction and diagnosis, contributing to personalised medicine and improving our ability to interpret genetic variations in relation to disease.

Planned Secondments

UCAM (Blundell) in year 2 (2 months) and CUT (Lakatos) in year 3 (1 month) to receive training on complex systems mathematical modelling.
IP (Berthelot) in year 4 (1 week) to learn about GWAS and primate research.

Enrolment in doctoral programs

PhD in Biomedicine from Universitat Pompeu Fabra