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ORCIDNatal A. W. van Riel
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2020 – today
- 2024
[j16]Ysanne M. Pasveer, Ömrüm Aydin
, Albert K. Groen, Abraham S. Meijnikman, Max Nieuwdorp, Victor E. A. Gerdes, Natal A. W. van Riel:
Does GLP-1 cause post-bariatric hypoglycemia: 'Computer says no'. Comput. Methods Programs Biomed. 257: 108424 (2024)- [c6]Danilo Ferreira de Carvalho, Uzay Kaymak, Pieter Van Gorp, Natal A. W. van Riel:
An Interpretability-Driven Fuzzy Modeling Methodology for Personalized Meal Detection. FUZZ 2024: 1-8 - [c5]Roy R. M. Van Mierlo, R. Arthur Bouwman, Natal A. W. van Riel:
Reproducing and Improving One-Dimensional Convolutional Neural Networks for Arterial Blood Pressure-Based Cardiac Output Estimation. MeMeA 2024: 1-6 - 2023
- [j15]Danilo Ferreira de Carvalho, Uzay Kaymak, Pieter Van Gorp, Natal A. W. van Riel:
Data-driven meal events detection using blood glucose response patterns. BMC Medical Informatics Decis. Mak. 23(1): 282 (2023) - [j14]Meike A. C. van den Eijnden, Jonna A. van der Stam, R. Arthur Bouwman, Eveline H. J. Mestrom, Wim F. J. Verhaegh, Natal A. W. van Riel, Lieke G. E. Cox:
Machine Learning for Postoperative Continuous Recovery Scores of Oncology Patients in Perioperative Care with Data from Wearables. Sensors 23(9): 4455 (2023) - [c4]Ana Moreira, Maren Philipps, Natal A. W. van Riel:
Parameter Estimation Of A Physiological Diabetes Model Using Neural Networks. CIBCB 2023: 1-8 - 2022
- [c3]Danilo Ferreira de Carvalho, Uzay Kaymak, Pieter Van Gorp, Natal A. W. van Riel:
Population and Individual Level Meal Response Patterns in Continuous Glucose Data. IPMU (2) 2022: 235-247 - 2021
- [j13]Balázs Erdos, Bart van Sloun, Michiel E. Adriaens, Shauna D. O'Donovan, Dominique Langin, Arne Astrup, Ellen E. Blaak, Ilja C. W. Arts, Natal A. W. van Riel:
Personalized computational model quantifies heterogeneity in postprandial responses to oral glucose challenge. PLoS Comput. Biol. 17(3) (2021) - 2020
- [j12]Andrea Cabbia, Peter A. J. Hilbers, Natal A. W. van Riel:
A Distance-Based Framework for the Characterization of Metabolic Heterogeneity in Large Sets of Genome-Scale Metabolic Models. Patterns 1(6): 100080 (2020) - [j11]Andrea Cabbia, Peter A. J. Hilbers, Natal A. W. van Riel:
A Distance-Based Framework for the Characterization of Metabolic Heterogeneity in Large Sets of Genome-Scale Metabolic Models. Patterns 1(9): 100174 (2020)
2010 – 2019
- 2019
- [j10]Yvonne J. W. Rozendaal, Yanan Wang, Peter A. J. Hilbers, Natal A. W. van Riel:
Computational modelling of energy balance in individuals with Metabolic Syndrome. BMC Syst. Biol. 13(1): 24:1-24:14 (2019) - [j9]Shauna D. O'Donovan, Michael Lenz, Roel G. Vink, Nadia J. T. Roumans, Theo M. de Kok, Edwin C. M. Mariman, Ralf L. M. Peeters, Natal A. W. van Riel, Marleen A. van Baak, Ilja C. W. Arts:
A computational model of postprandial adipose tissue lipid metabolism derived using human arteriovenous stable isotope tracer data. PLoS Comput. Biol. 15(10) (2019) - [p1]Dragan Bosnacki, Natal A. W. van Riel, Mitko Veta:
Deep Learning with Convolutional Neural Networks for Histopathology Image Analysis. Automated Reasoning for Systems Biology and Medicine 2019: 453-469 - 2018
- [j8]Yvonne J. W. Rozendaal, Yanan Wang, Yared Paalvast, Lauren L. Tambyrajah, Zhuang Li, Ko Willems van Dijk, Patrick C. N. Rensen, Jan A. Kuivenhoven, Albert K. Groen, Peter A. J. Hilbers, Natal A. W. van Riel:
In vivo and in silico dynamics of the development of Metabolic Syndrome. PLoS Comput. Biol. 14(6) (2018) - 2014
- [j7]Joep Vanlier, Christian A. Tiemann, Peter A. J. Hilbers, Natal A. W. van Riel:
Optimal experiment design for model selection in biochemical networks. BMC Syst. Biol. 8: 20 (2014) - [j6]Fianne L. P. Sips, Christian A. Tiemann, Maaike H. Oosterveer, Albert K. Groen, Peter A. J. Hilbers, Natal A. W. van Riel:
A Computational Model for the Analysis of Lipoprotein Distributions in the Mouse: Translating FPLC Profiles to Lipoprotein Metabolism. PLoS Comput. Biol. 10(5) (2014) - 2013
- [j5]Christian A. Tiemann, Joep Vanlier, Maaike H. Oosterveer, Albert K. Groen, Peter A. J. Hilbers, Natal A. W. van Riel:
Parameter Trajectory Analysis to Identify Treatment Effects of Pharmacological Interventions. PLoS Comput. Biol. 9(8) (2013) - 2012
- [j4]Joep Vanlier, Christian A. Tiemann, Peter A. J. Hilbers, Natal A. W. van Riel:
An integrated strategy for prediction uncertainty analysis. Bioinform. 28(8): 1130-1135 (2012) - [j3]Joep Vanlier, Christian A. Tiemann, Peter A. J. Hilbers, Natal A. W. van Riel:
A Bayesian approach to targeted experiment design. Bioinform. 28(8): 1136-1142 (2012) - 2011
- [j2]Christian A. Tiemann, Joep Vanlier, Peter A. J. Hilbers, Natal A. W. van Riel:
Parameter adaptations during phenotype transitions in progressive diseases. BMC Syst. Biol. 5: 174 (2011)
2000 – 2009
- 2007
- [c2]M. W. J. M. Musters, Hidde de Jong, P. P. J. van den Bosch, Natal A. W. van Riel:
Qualitative Analysis of Nonlinear Biochemical Networks with Piecewise-Affine Functions. HSCC 2007: 727-730 - 2006
- [j1]Natal A. W. van Riel:
Dynamic modelling and analysis of biochemical networks: mechanism-based models and model-based experiments. Briefings Bioinform. 7(4): 364-374 (2006) - 2002
- [c1]Natal A. W. van Riel, Ger J. van der Vusse:
Computational analysis of calcium transients in the intact rat heart; model identification. CDC 2002: 2536-2537
Coauthor Index
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