School of Medicine
Showing 11-20 of 37 Results
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Laurens van de Wiel
Postdoctoral Scholar, Cardiovascular Medicine
BioLaurens van de Wiel is Dutch scientist from Berghem, The Netherlands. Laurens spent his undergrad in Software Development (BSc, Avans Hogeschool ‘s-Hertogenbosch) and Computing Science (MSc, Radboud University Nijmegen). Laurens continued his career at a start-up, where he created large-scale, real-time analytical software. Laurens continued on his academic trajectory at the Radboudumc in Nijmegen, where he started his PhD in bioinformatics.
During his PhD, Laurens integrated genetic data with protein 3D structures and protein domains. He utilized the skills he obtained before setting out on his academic trajectory; building large-scale, robust, reliable software. Exemplified by the MetaDome Web server (https://stuart.radboudumc.nl/metadome/). During his PhD, he developed novel methodologies for the interpretation of genetic variants of unknown clinical significance and, by integrating structural and evolutionary biology with genomics, Laurens identified 36 novel disease-gene associations for developmental disorders. These discoveries enabled diagnosis for over 500 families worldwide.
Laurens’ areas of expertise are (bioinformatic) software development, data integration of genetic variation with other omics, and his research aims are:
1.) Lessons long-learned in computer science aid computational biology
2.) Multi-omic data integration allows the impact measurement of genetic variation
3.) Diagnosing undiagnosed disorders will uncover novel insights into biology.
4.) International and multidisciplinary collaborations are key in diagnosing rare disorders.
At Stanford University, under guidance of Dr. Matthew Wheeler, he is conducting his postdoctoral studies in line with his research aims. -
Henk van Voorst
Postdoctoral Scholar, Radiology
BioDr. van Voorst is a postdoctoral scholar in Radiology studying the interfaces of artificial intelligence and neuroradiological imaging in stroke. Originally educated as an MD, Dr. van Voorst gained additional degrees in Finance and Data Science. As a PhD student, Dr. van Voorst focused on cost-effectiveness modeling and developed machine learning and deep learning algorithms with applications in acute ischemic stroke imaging. In his current research, Dr. van Voorst develops artificial intelligence algorithms to automatically extract information from arteries and veins in radiological stroke imaging.
