Dennis Beest
Statistician
Randstad, Netherlands
Summary
👤
Senior🎓
Top SchoolDennis Beest is a statistician with nine years of applied research experience translating complex biological and infectious-disease problems into robust statistical and machine-learning solutions. He has led statistical consulting and methodological development for multicentre genomics and omics projects, combining penalized regression, random forests and empirical-Bayes inspired approaches to improve high-dimensional prediction. His background in mathematical modelling of plant, veterinary and human diseases gives him a rare blend of mechanistic and data-driven perspectives, and he routinely implements bespoke methods in R. At Wageningen University & Research he continues to focus on genomics-driven questions while maintaining a strong track record of producing pragmatic, review‑praised statistical analyses. A detail that sets him apart is his experience integrating low-dimensional clinical data with high-dimensional molecular data to test added predictive value rather than relying on single-method pipelines.
9 years of coding experience
Agro Systems Engineering (Dutch: Agrosysteemkunde), Specialisation - Operations Research, Agro Systems Engineering (Dutch: Agrosysteemkunde), Specialisation - Operations Research at Wageningen University
English, German, Dutch
Github Skills (18)
correlation4
microbiome3
sequencing3
normalization3
steambot2
computational-biology2
absolute2
biodiversity2
meta-analysis2
customisation2
gift2
azerothcore2
steam-api1
user-interface1
steamworks1
Programming languages (2)
Github contributions (5)
DennisBeest/CoRF
Apr 2017 - Feb 2020
Contributions:37 commits, 39 pushes, 1 branch in 2 years 10 months
DennisBeest/Log-ratio-analysis-of-microbiome-data-code-paper-
Dec 2020 - Jul 2024
Contributions:13 pushes, 1 branch in 3 years 8 months
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