Laurens van de Wiel

Laurens van de Wiel

Bioinformatics Research Scientist

Professional Profile

I am a post-doctoral researcher at Stanford University under supervision of Matthew Wheeler and Stephen Montgomery. My research focuses on understanding the entire spectrum of genetic variation effects on protein function and structure in order to decipher molecular mechanisms of disease.

My post-doctoral work centers on developing novel software methodologies which combine multi-omics data to interpret the functional impact of genetic variants in undiagnosed patients. I am part of the Undiagnosed Disease Network (UDN) at Stanford Center for Undiagnosed Diseases (CUD), Genomics Research to Elucidate the Genetics of Rare Diseases (GREGoR) consortium at GREGoR Stanford Site (GSS), and the Molecular Transducers of Physical Activity Consortium (MoTrPAC) at the Bioinformatics Center (BIC).

Before joining Stanford. I was received my Ph.D. in 2021 at the Radboud University Medical Center under supervision of Christian Gilissen, Gert Vriend, and Joris Veltman. I received my MSc degree in 2014 at Radboud University under supervision of Tom Heskes, Evgeni Levin, and Armand Paauw. Before my Ph.D, I worked as a Data Scientist at FLXone, where I developed machine learning solutions within a large-scale, real-time infrastructure.

Research

I am interested in a variety of topics in Bioinformatics and Computer Science. In particular, I am interested in the application of Artificial Intelligence and Statistical Modelling to analyse human (Rare) Mendelian Disease Genetics, Evolutionary Comparative Genomics, Protein Domain Homology, and Molecular Structures.

A list of my publications can be found here.
My Ph.D thesis - “Interpreting genomic variation using protein structures and evolutionary information” - available here
My MSc Thesis - “Differentiating Shigella from E. coli using hierarchical feature selection on MALDI-TOF MS Data” - available here .

Some of my work has been featured in the media, see here.

Awards