Dr Alessia David is a Lecturer in Bioinformatics and Data Intensive Biology/Clinical Research Fellow in the Centre for Integrative System Biology and Bioinformatics at Imperial College London and a Honorary Consultant Physician at Imperial College NHS Trust. She graduated with honours in Medicine from the University of Rome La Sapienza and completed her specialist training in Endocrinology and Metabolic Diseases. She holds a PhD in Molecular Endocrinology from the William Harvey Research Institute, Queen Mary University London and an MSc in Bioinformatics and System Biology from Imperial College London. In 2013, she was awarded an MRC fellowship in Biomedical Informatics. After completing her fellowship, she continued her research work as a Clinical Research Fellow at Imperial College London. Over the last 10 years, she has been engaged in identifying the genetic and molecular mechanisms contributing to human diseases by using a range of mathematical and bioinformatics approaches and has published extensively on a wide range of genetic conditions. She has received funding from the MRC, Wellcome Trust and Imperial Health Charity.
Dr Alessia David and Prof Michael Sternberg co-developed the following resources for variant prediction:
Missense3D - an algorithm to predict the structural changes introduced by an amino acid substitution. It is applicable for the analysis of both experimental and predicted 3D protein structures.
Missense3D-DB - a database of precomputed structural predictions for 4 million human missense variants
PhyreRisk - a dynamic web application developed to enable the exploration and mapping of genetic variants onto experimental and predicted structures of proteins and protein complexes
et al., 2023, GWAS of random glucose in 476,326 individuals provide insights into diabetes pathophysiology, complications and treatment stratification, Nature Genetics, Vol:55, ISSN:1061-4036, Pages:1448-1461
et al., 2023, Rare variants in the MECP2 gene in girls with central precocious puberty: a translational cohort study, The Lancet Diabetes & Endocrinology, Vol:11, ISSN:2213-8587, Pages:545-554
et al., 2023, Missense3D-PPI: a web resource to predict the impact of missense variants at protein interfaces using 3D structural data, Journal of Molecular Biology, Vol:435, ISSN:0022-2836, Pages:1-9
et al., 2023, Somatic mutations of CADM1 in aldosterone-producing adenomas and gap junction-dependent regulation of aldosterone production, Nature Genetics, Vol:55, ISSN:1061-4036, Pages:1009-1021
David A, Sternberg MJE, 2023, Protein structure-based evaluation of missense variants: Resources, challenges and future directions., Current Opinion in Structural Biology, Vol:80, ISSN:0959-440X, Pages:1-8
et al., 2023, A new web resource to predict the impact of missense variants at protein interfaces using 3D structural data: Missense3D-PPI
et al., 2022, A common TMPRSS2 variant has a protective effect against severe COVID-19, Current Research in Translational Medicine, Vol:70, ISSN:2452-3186
et al., 2021, The AlphaFold database of protein structures: a biologist’s guide, Journal of Molecular Biology, Vol:434, ISSN:0022-2836, Pages:167336-167336
et al., 2021, Missense3D-DB web catalogue: an atom-based analysis and repository of 4M human protein-coding genetic variants, Human Genetics, Vol:140, ISSN:0340-6717, Pages:805-812
et al., 2020, Inborn errors of type I IFN immunity in patients with life-threatening COVID-19, Science, Vol:370, ISSN:0036-8075, Pages:1-16