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2020 – today
- 2021
[j17]Pascal Schlosser
, Jochen Knaus, Maximilian Schmutz, Konstanze Döhner, Christoph Plass, Lars Bullinger, Rainer Claus, Harald Binder, Michael Lübbert, Martin Schumacher:
Netboost: Boosting-Supported Network Analysis Improves High-Dimensional Omics Prediction in Acute Myeloid Leukemia and Huntington's Disease. IEEE ACM Trans. Comput. Biol. Bioinform. 18(6): 2635-2648 (2021)
2010 – 2019
- 2018
- [j16]Regina Brinster, Anna Köttgen, Bamidele O. Tayo, Martin Schumacher, Peggy Sekula:
Control procedures and estimators of the false discovery rate and their application in low-dimensional settings: an empirical investigation. BMC Bioinform. 19(1): 78:1-78:10 (2018) - 2016
- [j15]Stefanie Hieke, Axel Benner, Richard F. Schlenl, Martin Schumacher, Lars Bullinger, Harald Binder:
Integrating multiple molecular sources into a clinical risk prediction signature by extracting complementary information. BMC Bioinform. 17: 327 (2016) - 2014
- [j14]Stefanie Hieke, Harald Binder, Alexandra Nieters, Martin Schumacher:
minPtest: a resampling based gene region-level testing procedure for genetic case-control studies. Comput. Stat. 29(1): 51-63 (2014) - 2013
- [j13]Veronika Reiser, Christine Porzelius, Susanne Stampf, Martin Schumacher, Harald Binder:
Can matching improve the performance of boosting for identifying important genes in observational studies? Comput. Stat. 28(1): 37-49 (2013) - 2011
- [j12]Martin Wolkewitz, Martin Schumacher:
Simulating and analysing infectious disease data in a heterogeneous population with migration. Comput. Methods Programs Biomed. 104(2): 29-36 (2011) - [j11]Arthur Allignol, Martin Schumacher, Jan Beyersmann:
Estimating summary functionals in multistate models with an application to hospital infection data. Comput. Stat. 26(2): 181-197 (2011) - [j10]Christine Porzelius, Martin Schumacher, Harald Binder:
The benefit of data-based model complexity selection via prediction error curves in time-to-event data. Comput. Stat. 26(2): 293-302 (2011) - 2010
- [j9]Christine Porzelius, Martin Schumacher, Harald Binder:
Sparse regression techniques in low-dimensional survival data settings. Stat. Comput. 20(2): 151-163 (2010)
2000 – 2009
- 2009
- [j8]Christine Porzelius, Harald Binder, Martin Schumacher:
Parallelized prediction error estimation for evaluation of high-dimensional models. Bioinform. 25(6): 827-829 (2009) - [j7]Harald Binder, Arthur Allignol, Martin Schumacher, Jan Beyersmann:
Boosting for high-dimensional time-to-event data with competing risks. Bioinform. 25(7): 890-896 (2009) - [j6]Harald Binder, Martin Schumacher:
Incorporating pathway information into boosting estimation of high-dimensional risk prediction models. BMC Bioinform. 10 (2009) - 2008
- [j5]Harald Binder, Martin Schumacher:
Comment on "network-constrained regularization and variable selection for analysis of genomic data". Bioinform. 24(21): 2566-2568 (2008) - [j4]Harald Binder, Martin Schumacher:
Allowing for mandatory covariates in boosting estimation of sparse high-dimensional survival models. BMC Bioinform. 9 (2008) - 2007
- [j3]Martin Schumacher, Harald Binder, Thomas Gerds:
Assessment of survival prediction models based on microarray data. Bioinform. 23(14): 1768-1774 (2007) - 2006
- [j2]Norbert Holländer, Martin Schumacher:
Estimating the functional form of a continuous covariate's effect on survival time. Comput. Stat. Data Anal. 50(4): 1131-1151 (2006) - 2001
- [j1]Joachim Spreer, Peter Martin, Wark M. Greenlee, Rainer Wohlfarth, Axel Hammen, Sebastian M. Arnold, Martin Schumacher:
Functional MRI in Patients with Band Heterotopia. NeuroImage 14(2): 357-365 (2001) - 2000
- [c3]Willi Sauerbrei, Martin Schumacher:
Bootstrap and Cross-Validation to Assess Complexity of Data-Driven Regression Models. ISMDA 2000: 234-241
1990 – 1999
- 1994
- [c2]C. Schmoor, M. Olschewski, Martin Schumacher:
Randomisierte und nicht-randomisierte Patienten in klinischen Therapiestudien: Erfahrungen mit dem CCS-Design. GMDS 1994: 444-449 - [c1]Erika Graf, Willi Sauerbrei, Martin Schumacher, Claudia Schmoor:
Berücksichtigung prognostischer Faktoren bei der Planung von Therapiestudien. GMDS 1994: 475-480
Coauthor Index
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