Rob ter Horst

Postdoctoral researcher

1. who studies the immune system using the computer. I specialise in bioinformatics, which means I study biology using machine learning and statistics.

2. who is life-logging everything. I am quite possibly doing the ultimate "quantified self", which means I measure everything in life. My measurements take more than 11 hours a week and include a weekly brain MRI, sleep EEG and gut microbiome composition. ​ Check out my YouTube channel if you want to know more!

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This is me

 
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I am a scientist at the CeMM Research Center for Molecular Medicine

I am interested in the analysis of omics data and I have a fascination for for statistics and machine learning. I personally try to keep a pragmatic outlook on research, starting with simple approaches and increasing complexity where needed. In my Chemistry education, I specialized in computational Chemistry and later in bioinformatics. I further developed my knowledge of machine learning while working in the fields of metabolomics and cellular image analysis. In my PhD research I use statistics and pattern recognition to identify factors that shape our immune system in health and disease. In this research I use omics data, like genomics, transcriptomics and metabolomics.

Also, to make science more accessible to the public, I write blogs and create vlogs about science.

Bioinformatics  YouTube 
Data analysis 

 R   Science outreach

Python    Fun  Creative

Publications

1.         ter Horst, R., et al., Sex-specific regulation of inflammation and metabolic syndrome in obesity. Arteriosclerosis, Thrombosis, and Vascular Biology, in press(July).

2.         Zwaag, J., et al., Involvement of Lactate and Pyruvate in the Anti-Inflammatory Effects Exerted by Voluntary Activation of the Sympathetic Nervous System. Metabolites, 2020. 10(4): p. 148.

3.         Sánchez-Maldonado, J.M., et al., NFKB2 polymorphisms associate with the risk of developing rheumatoid arthritis and response to TNF inhibitors: Results from the REPAIR consortium. Scientific Reports, 2020. 10(1): p. 1-13.

4.         Gonçalves, S.M., et al., Phagosomal removal of fungal melanin reprograms macrophage metabolism to promote antifungal immunity. Nature communications, 2020. 11(1): p. 1-15.

5.         van Laarhoven, A., et al., Immune cell characteristics and cytokine responses in adult HIV-negative tuberculous meningitis: an observational cohort study. Scientific reports, 2019. 9(1): p. 1-11.

6.         Sánchez-Maldonado, J.M., et al., Steroid hormone-related polymorphisms associate with the development of bone erosions in rheumatoid arthritis and help to predict disease progression: Results from the REPAIR consortium. Scientific reports, 2019. 9(1): p. 1-16.

7.         Raijmakers, R.P., et al., A possible role for mitochondrial-derived peptides humanin and MOTS-c in patients with Q fever fatigue syndrome and chronic fatigue syndrome. Journal of translational medicine, 2019. 17(1): p. 157.

8.         Grondman, I., et al., Frontline Science: Endotoxin‐induced immunotolerance is associated with loss of monocyte metabolic plasticity and reduction of oxidative burst. Journal of leukocyte biology, 2019. 106(1): p. 11-25.

9.         Domínguez-Andrés, J., et al., The itaconate pathway is a central regulatory node linking innate immune tolerance and trained immunity. Cell metabolism, 2019. 29(1): p. 211-220. e5.

10.       van den Munckhof, I., et al., Role of gut microbiota in chronic low‐grade inflammation as potential driver for atherosclerotic cardiovascular disease: a systematic review of human studies. Obesity Reviews, 2018. 19(12): p. 1719-1734.

11.       Steenbergen, R., et al., Establishing normal metabolism and differentiation in hepatocellular carcinoma cells by culturing in adult human serum. Scientific reports, 2018. 8(1): p. 1-14.

12.       Ilardo, M.A., et al., Physiological and Genetic Adaptations to Diving in Sea Nomads. Cell, 2018. 173(3): p. 569-580. e15.

13.       Bekkering, S., et al., Metabolic induction of trained immunity through the mevalonate pathway. Cell, 2018. 172(1-2): p. 135-146. e9.

14.       Domínguez-Andrés, J., et al., Rewiring monocyte glucose metabolism via C-type lectin signaling protects against disseminated candidiasis. PLoS pathogens, 2017. 13(9): p. e1006632.

15.       ter Horst, R., et al., Host and environmental factors influencing individual human cytokine responses. Cell, 2016. 167(4): p. 1111-1124. e13.

16.       Schirmer, M., et al., Linking the human gut microbiome to inflammatory cytokine production capacity. Cell, 2016. 167(4): p. 1125-1136. e8.

17.       Oosting, M., et al., Functional and genomic architecture of Borrelia burgdorferi-induced cytokine responses in humans. Cell Host & Microbe, 2016. 20(6): p. 822-833.

18.       Netea, M.G., et al., Understanding human immune function using the resources from the Human Functional Genomics Project. Nature Medicine, 2016. 22(8): p. 831-833.

19.       Arts, R.J., et al., Glutaminolysis and fumarate accumulation integrate immunometabolic and epigenetic programs in trained immunity. Cell Metabolism, 2016. 24(6): p. 807-819.

20.       van der Lee, R., et al., Integrative genomics-based discovery of novel regulators of the innate antiviral response. PLoS computational biology, 2015. 11(10).

21.       Ljosa, V., et al., Comparison of methods for image-based profiling of cellular morphological responses to small-molecule treatment. Journal of biomolecular screening, 2013. 18(10): p. 1321-1329.

 

Recent YouTube Videos

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© 2020 by Rob ter Horst