Dr Alfredo Iacoangeli
Research Fellow in Translational Bioinformatics
After a career in Biophysics, Dr. Alfredo Iacoangeli accepted his PhD “cum laude” in Life Sciences in January 2016 from “Sapienza” University of Rome where he worked on structural bioinformatics with a particular focus on protein structure prediction and protein-peptide interaction. He joined King’s College London in March 2016 and he is now the Bioinformatics lead of a joint project between the Department of Basic and Clinical Neuroscience and the Health Informatics Unit at the Institute of Psychiatry, Psychology & Neuroscience at King’s College London. The aim of this project is twofold: 1) the development of a high throughput gene, environment and epigenetics database and analysis system for international MND/ALS research; 2) the use of large multi-omics datasets to identify subgroups MND/ALS patients with homogeneous disease causes and clinical phenotype, and to gain new insights into the disease pathogenesis. Dr. Iacoangeli is first author of several scientific articles in the field of Structural and Genomic Bioinformatics and MND/ALS genetics.
Bioinformatics (both genomics and structural biology); Genetics of complex diseases; Big Biodata; Precision medicine; Machine learning.
- DNAscan2: a versatile, scalable, and user-friendly analysis pipeline for human next-generation sequencing data
- Large-scale Analyses of CAV1 and CAV2 Suggest Their Expression is Higher in Post-mortem ALS Brain Tissue and Affects Survival
- Large-scale analyses of CAV1 and CAV2 suggest their expression is higher in post-mortem ALS brain tissue and affects survival
- An assessment of bioinformatics tools for the detection of human endogenous retroviral insertions in short-read genome sequencing data
- The SOD1-mediated ALS phenotype shows a decoupling between age of symptom onset and disease duration