Upamanyu Ghose
MSc
DPhil Student
Development of machine learning methods to analyse multi-omic data for Alzheimer's disease
I am a member of the bioinformatics team in the Translational Neuroscience and Dementia Research Group, specialising in deep learning applied to genomic data. I completed my MSc in Computer Science at Oxford. While computer science and deep learning are the areas I specialise in, neuroscience is the area that deeply fascinates me. I believe that bridging the two fields together has the potential of novel and interesting findings that can better explain unanswered questions of neuroscience.
My current work revolves around using artificial neural networks (ANNs) to better understand the genetic factors contributing to neurodegenerative diseases like Alzheimer's disease. Traditional methods of GWAS using linear models have successfully identified several risk loci for a wide range of diseases and other phenotypes, but a large part of the missing heritability of diseases like Alzheimer's remains unexplained. To circumvent this issue, ANNs can be used to identify and incorporate non-linear patterns that are present in genomic data, such as the interaction between different genetic loci, allowing them to understand such diseases better than linear models.
Key publications
Multimodal deep learning enhances genomic risk prediction for cardiometabolic diseases in UK Biobank
Preprint
Zhu T. et al, (2025)
Genome-wide association neural networks identify genes linked to family history of Alzheimer's disease.
Journal article
Ghose U. et al, (2024), Brief Bioinform, 26
Proteomic aging clock predicts mortality and risk of common age-related diseases in diverse populations.
Journal article
Argentieri MA. et al, (2024), Nat Med, 30, 2450 - 2460
Recent publications
The relationship between anaemia, haemoglobin levels, and cognitive function: Evidence in two population-based cohorts from India and the United States.
Journal article
Winchester LM. et al, (2025), Neurobiol Dis, 216
Mitochondria-derived nuclear ATP surge protects against confinement-induced proliferation defects.
Journal article
Ghose R. et al, (2025), Nat Commun, 16
Multimodal deep learning enhances genomic risk prediction for cardiometabolic diseases in UK Biobank
Preprint
Zhu T. et al, (2025)
Semaphorin 3E alters the secretory function of pancreatic islet beta cells
Conference paper
Hastoy B. et al, (2025), DIABETIC MEDICINE, 42
