Publications of year 2018

Articles in journal or book chapters

Simone Lederer, Tjeerd Dijkstra, and Tom Heskes. Additive dose response models: Explicit formulation and the Loewe additivity consistency condition. Frontiers in Pharmacology, 9:31, 2018.

@ARTICLE{lederer2018,
AUTHOR = {Simone Lederer and Tjeerd Dijkstra and Tom Heskes},
URL = {https://doi.org/10.3389/fphar.2018.00031},
JOURNAL = {Frontiers in Pharmacology},
VOLUME = 9,
PAGES = 31,
TITLE = {Additive dose response models: {E}xplicit formulation and the {L}oewe additivity consistency condition},
YEAR = {2018} 
}

Kees Okkersen, Cecilia Jimenez-Moreno, Stephan Wenninger, Ferroudja Daidj, ..., Tom Heskes, ..., and Juliane Dittrich. Cognitive behavioural therapy with optional graded exercise therapy in patients with severe fatigue with myotonic dystrophy type 1: a multicentre, single-blind, randomised trial. The Lancet Neurology, 17(8):671-680, 2018.

@ARTICLE{OKKERSEN2018671,
TITLE = {Cognitive behavioural therapy with optional graded exercise therapy in patients with severe fatigue with myotonic dystrophy type 1: a multicentre, single-blind, randomised trial},
AUTHOR = {Kees Okkersen and Cecilia Jimenez-Moreno and Stephan Wenninger and Ferroudja Daidj and ... and Tom Heskes and ... and Juliane Dittrich},
JOURNAL = {The Lancet Neurology},
VOLUME = 17,
NUMBER = 8,
PAGES = {671-680},
YEAR = 2018,
URL = {https://doi.org/10.1016/S1474-4422(18)30203-5} 
}

Markus Peters, Maytal Saar-Tsechansky, Wolfgang Ketter, Sinead Williamson, Perry Groot, and Tom Heskes. A scalable preference model for autonomous decision-making. Machine Learning, 107:1039-1068, 2018.

@ARTICLE{Peters2018,
AUTHOR = {Peters, Markus and Saar-Tsechansky, Maytal and Ketter, Wolfgang and Williamson, Sinead and Groot, Perry and Heskes, Tom},
TITLE = {A scalable preference model for autonomous decision-making},
JOURNAL = {Machine Learning},
VOLUME = {107},
PAGES = {1039-1068},
YEAR = {2018},
URL = {https://doi.org/10.1007/s10994-018-5705-5} 
}

Ridho Rahmadi, Perry Groot, and Tom Heskes. The stablespec package for causal discovery on cross-sectional and longitudinal data in R. Neurocomputing, 275:2440-2443, 2018.

@ARTICLE{Rahmadi2018a,
AUTHOR = {Rahmadi, Ridho and Groot, Perry and Heskes, Tom},
TITLE = {The stablespec package for causal discovery on cross-sectional and longitudinal data in R},
JOURNAL = {Neurocomputing},
YEAR = {2018},
VOLUME = 275,
PAGES = {2440-2443},
URL = {https://doi.org/10.1016/j.neucom.2017.10.064} 
}

Ridho Rahmadi, Perry Groot, Marieke van Rijn, Jan van den Brand, Marianne Heins, Hans Knoop, Tom Heskes, the Alzheimer's Disease Neuroimaging Initiative, the MASTERPLAN Study Group, and the OPTIMISTIC consortium. Causality on longitudinal data: Stable specification search in constrained structural equation modeling. Statistical Methods in Medical Research, 27(12):3814-3834, 2018.

@ARTICLE{rahmadi2018b,
AUTHOR = {Ridho Rahmadi and Perry Groot and Marieke van Rijn and Jan van den Brand and Marianne Heins and Hans Knoop and Tom Heskes and the Alzheimer's Disease Neuroimaging Initiative and the MASTERPLAN Study Group and the OPTIMISTIC consortium},
TITLE = {Causality on longitudinal data: Stable specification search in constrained structural equation modeling},
JOURNAL = {Statistical Methods in Medical Research},
VOLUME = {27},
NUMBER = {12},
PAGES = {3814-3834},
YEAR = {2018},
URL = {https://doi.org/10.1177/0962280217713347} 
}

Bram Thijssen, Tjeerd Dijkstra, Tom Heskes, and Lodewyk Wessels. Bayesian data integration for quantifying the contribution of diverse measurements to parameter estimates. Bioinformatics, 34:803-811, 2018.

@ARTICLE{thijssen2018bayesian,
TITLE = {Bayesian data integration for quantifying the contribution of diverse measurements to parameter estimates},
AUTHOR = {Thijssen, Bram and Dijkstra, Tjeerd and Heskes, Tom and Wessels, Lodewyk},
JOURNAL = {Bioinformatics},
YEAR = {2018},
VOLUME = {34},
PAGES = {803-811},
URL = {https://doi.org/10.1093/bioinformatics/btx666} 
}

Christiaan de Leeuw, Sven Stringer, Ilona Dekkers, Tom Heskes, and Danielle Posthuma. Conditional and interaction gene-set analysis reveals novel functional pathways for blood pressure. Nature Communications, 9:3768, 2018.

@ARTICLE{leeuw2018,
TITLE = {Conditional and interaction gene-set analysis reveals novel functional pathways for blood pressure},
AUTHOR = {de Leeuw, Christiaan and Stringer, Sven and Dekkers, Ilona and Heskes, Tom and Posthuma, Danielle},
YEAR = 2018,
URL = {https://doi.org/10.1038/s41467-018-06022-6},
JOURNAL = {Nature Communications},
VOLUME = 9,
PAGES = 3768 
}

Conference articles

Ioan Gabriel Bucur, Tom van Bussel, Tom Claassen, and Tom Heskes. A Bayesian approach for inferring local causal structure in gene regulatory networks. In Václav Kratochvěl and Milan Studeny, editors, Proceedings of the Ninth International Conference on Probabilistic Graphical Models, volume 72 of Proceedings of Machine Learning Research, Prague, Czech Republic, pages 37-48, 11-14 Sep 2018. PMLR.

@INPROCEEDINGS{pmlr-v72-bucur18a,
TITLE = {A Bayesian approach for inferring local causal structure in gene regulatory networks},
AUTHOR = {Bucur, Ioan Gabriel and van Bussel, Tom and Claassen, Tom and Heskes, Tom},
BOOKTITLE = {Proceedings of the Ninth International Conference on Probabilistic Graphical Models},
PAGES = {37-48},
YEAR = {2018},
EDITOR = {Kratochv\'{i}l, V\'{a}clav and Studen\'{y}, Milan},
VOLUME = {72},
SERIES = {Proceedings of Machine Learning Research},
ADDRESS = {Prague, Czech Republic},
MONTH = {11-14 Sep},
PUBLISHER = {PMLR},
URL = {http://proceedings.mlr.press/v72/bucur18a/bucur18a.pdf} 
}

Ruifei Cui, Perry Groot, Moritz Schauer, and Tom Heskes. Learning the causal structure of copula models with latent variables. In UAI 2018, 2018.

@INPROCEEDINGS{cui18uai,
AUTHOR = {Ruifei Cui and Perry Groot and Moritz Schauer and Tom Heskes},
TITLE = {Learning the causal structure of copula models with latent variables},
BOOKTITLE = {UAI 2018},
YEAR = {2018},
URL = {http://auai.org/uai2018/proceedings/papers/65.pdf} 
}