Getuyg Data Analytics

I started Getuyg as a company to consults in artificial intelligence, data analysis, and data driven decision-making. Getuyg can consult on all parts of the process, modeling, large language models, compute hardware, data storage (both software and hardware), data curation and adaptation, data mining, data visualization, data modeling, and data driven decision making. I work both with open and closed source solutions. In technical jargon, I have an expertise working with deep learning, random forests, dimensionality reduction, multi-objective optimization, text mining, and GPU computing.

On the name and logo...

The name Getuyg is an old Dutch term used to indicate ‘a miner’s tools’. As there are many similarities in data analysis and traditional mining (even found in the term ‘data mining’) this seemed appropriate.

Gerard JP van Westen, PhD

I hold a PhD in cheminformatics and have a proven track record in data mining with over 20 years of experience. I have published over 130 peer-reviewed papers, but more importantly, I worked in an NGO environment (EMBL-EBI), a corporate environment (Janssen, pharmaceutical companies of Johnson & Johnson), and with corporate partners (Unilever, Syngenta, Merck, Bayer, and a number of start-up companies). I can quickly master new concepts, am a team player, and a strong communicator.

Interested?

If you have an interest in making use of Getuyg’s services, please contact me via email on . Alternatively, use the form in the contact section.

Selection of Publications

Review showing how AI can be used for natural product derived drugs (review): Artificial intelligence for natural product drug discovery.Mullowney, Michael W., Katherine R. Duncan, Somayah S. Elsayed, Neha Garg, Justin JJ van der Hooft, Nathaniel I. Martin, David Meijer et al. Nature Reviews Drug Discovery 22, no. 11 (2023): 895-916.

First paper to apply deep learning to large scale drug discovery data (AI): Beyond the hype: deep neural networks outperform established methods using a ChEMBL bioactivity benchmark set.Lenselink, Eelke B., Niels Ten Dijke, Brandon Bongers, George Papadatos, Herman WT Van Vlijmen, Wojtek Kowalczyk, Adriaan P. IJzerman, and Gerard JP Van Westen. Journal of cheminformatics 9, no. 1 (2017): 45.

AI approaches based on bothn chemical and target data (review): Proteochemometric modeling as a tool to design selective compounds and for extrapolating to novel targets, GJP van Westen, JK Wegner, AP IJzerman, HWT van Vlijmen, A Bender, MedChemComm 2 (1), 16-30

Data mining based personalized medicine for HIV patients (data mining): Significantly improved HIV inhibitor efficacy prediction employing proteochemometric models generated from antivirogram data, GJP van Westen, A Hendriks, JK Wegner, AP IJzerman, HWT van Vlijmen, et al, PLoS Comput Biol 9 (2), e1002899

Data based detection and prediction of Alzheimer’s disease (image analysis): Random Forest ensembles for detection and prediction of Alzheimer's disease with a good between-cohort robustness, AV Lebedev, E Westman, GJP Van Westen, MG Kramberger, et al, NeuroImage: Clinical 6, 115-125

Automatic classification of papers based on their abstracts (text mining): A document classifier for medicinal chemistry publications trained on the ChEMBL corpus, G Papadatos, GJP van Westen, S Croset, R Santos, S Trubian, et al, Journal of cheminformatics 6 (1), 40

View a complete list on Google scholar: https://scholar.google.nl/citations?user=H7farnwAAAAJ