Daniel Marbach
Daniel Marbach
Roche Pharma Research and Early Development, Basel, Switzerland
Verified email at - Homepage
Cited by
Cited by
Wisdom of crowds for robust gene network inference
D Marbach, JC Costello, R Küffner, NM Vega, RJ Prill, DM Camacho, ...
Nature methods 9 (8), 796-804, 2012
Identification of Functional Elements and Regulatory Circuits by Drosophila modENCODE
modENCODE Consortium, S Roy, J Ernst, PV Kharchenko, P Kheradpour, ...
Science 330 (6012), 1787-1797, 2010
Revealing strengths and weaknesses of methods for gene network inference
D Marbach, RJ Prill, T Schaffter, C Mattiussi, D Floreano, G Stolovitzky
Proceedings of the national academy of sciences 107 (14), 6286-6291, 2010
GeneNetWeaver: in silico benchmark generation and performance profiling of network inference methods
T Schaffter, D Marbach, D Floreano
Bioinformatics 27 (16), 2263-2270, 2011
Generating realistic in silico gene networks for performance assessment of reverse engineering methods
D Marbach, T Schaffter, C Mattiussi, D Floreano
Journal of computational biology 16 (2), 229-239, 2009
Towards a rigorous assessment of systems biology models: the DREAM3 challenges
RJ Prill, D Marbach, J Saez-Rodriguez, PK Sorger, LG Alexopoulos, ...
PloS one 5 (2), e9202, 2010
Fast and rigorous computation of gene and pathway scores from SNP-based summary statistics
D Lamparter, D Marbach, R Rueedi, Z Kutalik, S Bergmann
PLoS computational biology 12 (1), e1004714, 2016
Tissue-specific regulatory circuits reveal variable modular perturbations across complex diseases
D Marbach, D Lamparter, G Quon, M Kellis, Z Kutalik, S Bergmann
Nature methods 13 (4), 366-370, 2016
Network deconvolution as a general method to distinguish direct dependencies in networks
S Feizi, D Marbach, M Médard, M Kellis
Nature biotechnology 31 (8), 726-733, 2013
Assessment of network module identification across complex diseases
S Choobdar, ME Ahsen, J Crawford, M Tomasoni, T Fang, D Lamparter, ...
Nature methods 16 (9), 843-852, 2019
Chromatin three-dimensional interactions mediate genetic effects on gene expression
O Delaneau, M Zazhytska, C Borel, G Giannuzzi, G Rey, C Howald, ...
Science 364 (6439), eaat8266, 2019
Consortium D, Kellis M, Collins JJ, Stolovitzky G. Wisdom of crowds for robust gene network inference
D Marbach, JC Costello, R Kuffner, NM Vega, RJ Prill, DM Camacho, ...
Nat Methods 9 (8), 796-804, 2012
Predictive regulatory models in Drosophila melanogaster by integrative inference of transcriptional networks
D Marbach, S Roy, F Ay, PE Meyer, R Candeias, T Kahveci, CA Bristow, ...
Genome research 22 (7), 1334-1349, 2012
Online optimization of modular robot locomotion
D Marbach, AJ Ijspeert
IEEE International Conference Mechatronics and Automation, 2005 1, 248-253, 2005
Verification of systems biology research in the age of collaborative competition
P Meyer, LG Alexopoulos, T Bonk, A Califano, CR Cho, A De La Fuente, ...
Nature biotechnology 29 (9), 811-815, 2011
Co-evolution of configuration and control for homogenous modular robots
D Marbach, AJ Ijspeert
Proceedings of the eighth conference on intelligent autonomous systems (IAS8 …, 2004
Information-Theoretic Inference of Gene Networks Using Backward Elimination.
P Meyer, D Marbach, S Roy, M Kellis
BioComp, 700-705, 2010
Replaying the evolutionary tape: biomimetic reverse engineering of gene networks
D Marbach, C Mattiussi, D Floreano
Annals of the New York Academy of Sciences 1158 (1), 234-245, 2009
Combining multiple results of a reverse‐engineering algorithm: application to the DREAM five‐gene network challenge
D Marbach, C Mattiussi, D Floreano
Annals of the New York Academy of Sciences 1158 (1), 102-113, 2009
Genome-wide association between transcription factor expression and chromatin accessibility reveals regulators of chromatin accessibility
D Lamparter, D Marbach, R Rueedi, S Bergmann, Z Kutalik
PLoS computational biology 13 (1), e1005311, 2017
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