The 3DMolecular team is a spin-out from Swansea University and Moleculomics Ltd. Its aim is to build on our solid core of science, and take it forward with a strong commercial focus.
The team is a highly talented group of individuals, spanning biology, data science, and high performance computing. Members have worked on projects supported by major funding bodies, such as InnovateUK and NC3R's, and on commercial projects with clients as diverse and Unilever and the Ministry of Defence.
We have years of research published in peer reviewed journals, validating our methodologies and attesting to their accuracy and value, in academic and commercial environements. We excel in applying the latest develoments in Machine Learning and High Performance Computing to bioinformatics and molecular biology.
Our highly automated computational models can save you time and money, through giving you real insight into the systems you are studying earlier in the development cycle, helping you to develop better products, more quickly.
Jonathan has spent the last 20 years researching the structural and functional formation of proteins based upon their gene sequence. The tools and libraries generated by Jonathan’s research have supported world-leading research in unravelling the molecular phenotypes of several disorders, linking mutations to structural changes, mechanisms of disease and stratification of phenotypes. This research has been captured in over 40 journal publications since 2000.
John has 20 years experience in computational modelling, database architecture and programming. With a broad science and engineering background and enthusiasm for problem solving, John has built extensive IT experience involving a range of operating environments and programming languages which have been applied extensively in recent years to a number of High Performance Computing projects.
William has been involved in a number of high-profile projects for generation and subsequent analysis of molecular data for clients such as the Ministry of Defence, Unilever Plc and the Medical Research Council. He played a key role in the development of Human3DProteome, involving data analysis, interface design, database development, and Machine Learning for pharmaceutical R&D workflows.
Karl first studied physics, then scientific computing, and is now working towards a Ph.D. in bioinformatics. He uses Python and C to build simulations, data analysis pipelines, and machine learning models. He is also a Linux sysadmin for the 3DMolecular HPC cluster.
A keen data analyst with several years of experience in a variety of medical and general programming fields, James works on the design and development of tools to gather findings from numerous medical compound and protein databases. Through the use of R and MySQL languages James has been responsible as part of the team to extract and pre-process the information found within these databases, which in turn has led to the development of a comprehensive knowledgebase that link compound chemistry to biological activity and mechanisms of disease.