Dr Alfredo Iacoangeli

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 in the field of structural bioinformatics with a particular focus on protein structure prediction and protein-peptide interaction, Alfredo joined King’s College London in March 2016, and is now the lead of a joint programme 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 programme is twofold:

1) the development of computational approaches based on statistical, machine learning and bioinformatics methods, to study the biological basis of neurodegenerative diseases;

2) the use of large multi-omics and clinical datasets to identify subgroups of patients affected by neurodegenerative diseases with homogeneous disease causes and clinical phenotype, that can be used for precision approaches to clinical and biomedical research.

Dr Iacoangeli is first author of several scientific articles in the field of Structural and Genomic Bioinformatics, machine learning and MND/ALS genetics. 

 

Research Interests: 

• Bioinformatics
• Machine learning
• Genomics
• Motor Neurone Disease
• Neurodegeneration

Teaching:

• Bioinformatics, interpretation and data quality assurance in genome analysis 
• Advanced Bioinformatics
• Practical Structural Bioinformatics

Expertise and Public Engagement:

• Winner of the “ENCALS 2021 award” https://www.encals.eu/alfredo-iacoangeli-wins-the-encals-young-investigator-award-2021/
• Winner of the “Genes 2022 Young Investigator Award in Human Genomics and Genetic Diseases” https://www.kcl.ac.uk/news/dr-alfredo-iacoangeli-receives-genes-2022-young-investigator-award-in-human-genomics-and-genetic-diseases
• Project MinE Data Infrastructure working group Chair
• NIHR BioResource Centre Maudsley Rare Diseases lead
• Darby-Rimmer MND Foundation scientific advisory panel
• 2023 ALS Canada-Brain Canada Trainee Award review panel member 

Career Profile

Alfredo Iacoangeli - Pure Profile

Articles and Publications

• user-friendly analysis pipeline for human next-generation sequencing data
•  GEOexplorer: a webserver for gene expression analysis and visualisation." Nucleic Acids Research, 2022
• DGLinker: flexible knowledge-graph prediction of disease–gene associations
• Genome-wide Meta-analysis Finds the ACSL5-ZDHHC6 Locus Is Associated with ALS and Links Weight Loss to the Disease Genetics
• "A knowledge-based machine learning approach to gene prioritisation in amyotrophic lateral sclerosis." Genes, 2020