Reconstruction and Computational Modelling for Inherited Metabolic Diseases
Accelerating the diagnosis and personalising the management
of inherited metabolic diseases.
Key features of Recon4IMD
-
Overall objectives: Accelerate diagnosis and personalise management of inherited metabolic diseases.
-
Primary output: Clinically validated decision support tools enabling accelerated diagnosis and personalised management of inherited metabolic diseases, based on genomic, proteomic, and metabolomic data-driven computational models.
-
Sustainability: Development of academic technology to meet medical regulatory standards and a roadmap for exploitation within a European foundation to aid personalised diagnosis and management of inherited metabolic diseases.
-
Implemented by: A group of world-class scientists and clinicians from a diversity of disciplines who have collaborated multiple times and have a track record of leading key national and EU-funded initiatives to deliver high-impact results.
News & Events
Recon4IMD Clinical Connect Meeting,
Helsinki, Finland
Latest Publications
KinForm: kinetics-informed feature optimised representation models for enzyme kcat and KM prediction
Saleh Alwer & Ronan M.T. Fleming, 2026
Enzyme kinetic parameters, including the turnover number and Michaelis constant, are fundamental descriptors of enzymatic activity and are essential for quantitative modelling of metabolic systems. Experimental measurements remain limited in both scale and diversity, while existing prediction methods often rely on simple protein representations that limit performance on enzymes with low sequence similarity to training data.
