Physiology-informed regularisation enables training of universal differential equation systems for biological applications. 由 Max de Rooij, Balázs Erdős, Natal A W van Riel, Shauna D O'Donovan

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Analysis of high-dimensional metabolomics data with complex temporal dynamics using RM-ASCA. 由 Balázs Erdős, Johan A Westerhuis, Michiel E Adriaens, Shauna D O'Donovan, Ren Xie, Cécile M Singh-Povel, Age K Smilde, Ilja C W Arts

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E-DES-PROT: A novel computational model to describe the effects of amino acids and protein on postprandial glucose and insulin dynamics in humans 由 Bart van Sloun, Gijs H. Goossens, Balázs Erdõs, Shauna D. O’Donovan, Cécile M. Singh-Povel, Jan M.W. Geurts, Natal A.W. van Riel, Ilja C.W. Arts

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Leveraging continuous glucose monitoring for personalized modeling of insulin-regulated glucose metabolism 由 Balázs Erdős, Shauna D. O’Donovan, Michiel E. Adriaens, Anouk Gijbels, Inez Trouwborst, Kelly M. Jardon, Gijs H. Goossens, Lydia A. Afman, Ellen E. Blaak, Natal A. W. van Riel, Ilja C. W. Arts

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Application of transfer learning to predict drug-induced human in vivo gene expression changes using rat in vitro and in vivo data. 由 Shauna D O'Donovan, Rachel Cavill, Florian Wimmenauer, Alexander Lukas, Tobias Stumm, Evgueni Smirnov, Michael Lenz, Gokhan Ertaylan, Danyel G J Jennen, Natal A W van Riel, Kurt Driessens, Ralf L M Peeters, Theo M C M de Kok

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Quantifying the effect of nutritional interventions on metabolic resilience using personalized computational models 由 Shauna D. O’Donovan, Milena Rundle, E. Louise Thomas, Jimmy D. Bell, Gary Frost, Doris M. Jacobs, Anne Wanders, Ryan de Vries, Edwin C.M. Mariman, Marleen A. van Baak, Luc Sterkman, Max Nieuwdorp, Albert K. Groen, Ilja C.W. Arts, Natal A.W. van Riel, Lydia A. Afman

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