Objective: The aim of this research was to develop scalable and efficient algorithms, namely the in-silico GWAS (isGWAS) and leapfrog re-sampler (LRS), to overcome significant challenges in genome-wide association studies (GWAS). These challenges include the dependency on sensitive individual-level data, daunting computational demands arising from increasing cohort sizes and genetic variants, and limitations in traditional… Continue reading isGWAS: ultra-high-throughput, scalable and equitable inference of genetic associations with disease
Author: bioxcelerate
Blood protein levels predict leading incident morbidities and mortality in the UK Biobank
Objective: The overarching aim of this study was to explore the intricate relationship between the circulating proteome and age-related diseases and mortality using data from the UK Biobank. By analyzing blood data from 47,600 individuals over 16 years and linking it with electronic health records, our primary objective was to elucidate the associations between 1,468… Continue reading Blood protein levels predict leading incident morbidities and mortality in the UK Biobank
How Data Science is Impacting Drug Development: Q and A with Dr Chris Foley
Q: What role does data science have in drug development today?Data is driving change in the drug development space. Drug development is complex, resource-heavy, and very costly. Collaborating across diverse specialisms – clinicians, chemists, geneticists, epidemiologists – scientists contribute their expertise. Notably, data scientists play a critical role in research, utilizing state-of-the-art data science and… Continue reading How Data Science is Impacting Drug Development: Q and A with Dr Chris Foley