H. Binder

发表

Is there a role for statistics in artificial intelligence? pdf

Hans A. Kestler, Werner Brannath, Tim Friede, 2020, Advances in Data Analysis and Classification.

Flexible modelling of discrete failure time including time‐varying smooth effects

G. Tutz, H. Binder, Harald Binder, 2004, Statistics in medicine.

Generalized Additive Modeling with Implicit Variable Selection by Likelihood‐Based Boosting

G. Tutz, H. Binder, 2006, Biometrics.

Selection of important variables and determination of functional form for continuous predictors in multivariable model building

P. Royston, W. Sauerbrei, H. Binder, 2007, Statistics in medicine.

A DAG-based comparison of interventional effect underestimation between composite endpoint and multi-state analysis in cardiovascular trials

H. Binder, A. Bayés‐Genís, A. Jahn-Eimermacher, 2017, BMC Medical Research Methodology.

A coordinate-wise optimization algorithm for the Fused Lasso

H. Binder, M. Schumacher, Holger Hofling, 2010, 1011.6409.

Treatment-effect estimates adjusted for small-study effects via a limit meta-analysis.

G. Rücker, J. Carpenter, H. Binder, 2011, Biostatistics.

Transforming RNA-Seq Data to Improve the Performance of Prognostic Gene Signatures

Harald Binder, H. Binder, I. Zwiener, 2014, PloS one.

Prospective validation of a blood-based 9-miRNA profile for early detection of breast cancer in a cohort of women examined by clinical mammography

H. Binder, M. Lyng, A. R. Kodahl, 2016 .

Prospective validation of a blood‐based 9‐miRNA profile for early detection of breast cancer in a cohort of women examined by clinical mammography

H. Binder, H. Ditzel, M. Lyng, 2016, Molecular oncology.

Leveraging external knowledge on molecular interactions in classification methods for risk prediction of patients

Harald Binder, Christine Porzelius, Tim Beissbarth, 2011, Biometrical journal. Biometrische Zeitschrift.

On stability issues in deriving multivariable regression models

Anne-Laure Boulesteix, Harald Binder, Willi Sauerbrei, 2015, Biometrical journal. Biometrische Zeitschrift.

A boosting approach for adapting the sparsity of risk prediction signatures based on different molecular levels

Murat Sariyar, Harald Binder, Martin Schumacher, 2014, Statistical applications in genetics and molecular biology.

An overview of techniques for linking high‐dimensional molecular data to time‐to‐event endpoints by risk prediction models

H. Binder, M. Schumacher, C. Porzelius, 2011, Biometrical journal. Biometrische Zeitschrift.

Rank-based p-values for sparse high-dimensional risk prediction models fitted by componentwise boosting

H. Binder, M. Schumacher, C. Porzelius, 2009 .

Adapting Prediction Error Estimates for Biased Complexity Selection in High-Dimensional Bootstrap Samples

Harald Binder, Martin Schumacher, H. Binder, 2008, Statistical applications in genetics and molecular biology.

Fitting generalized additive models: A comparison of methods

Gerhard Tutz, November, Harald Binder, 2008 .

Promoter-proximal pausing mediated by the exon junction complex regulates splicing

H. Binder, Jean-Yves Roignant, Junaid Akhtar, 2019, Nature Communications.

CONNECTION SIGN ESTIMATION

H. Binder, M. Schumacher, Matthias Weber, 2020 .

The JuliaConnectoR: a functionally oriented interface for integrating Julia in R pdf

Maren Hackenberg, Harald Binder, Stefan Lenz, 2020, J. Stat. Softw..

Functional genomics indicate that schizophrenia may be an adult vascular-ischemic disorder

H. Binder, H. Binder, D. Wollschläger, 2015, Translational Psychiatry.

The Daim package – Diagnostic accuracy of classification models

Arbeitstagung, H. Binder, H. Kestler, 2011 .

Big data in medical science--a biostatistical view.

Harald Binder, Maria Blettner, H. Binder, 2015, Deutsches Arzteblatt international.

Introduction to statistical simulations in health research

A. Boulesteix, W. Sauerbrei, H. Binder, 2020, BMJ Open.

Stability analysis of an additive spline model for respiratory health data by using knot removal

W. Sauerbrei, H. Binder, 2009 .

Macrophage Activation in Acute Exacerbation of Idiopathic Pulmonary Fibrosis

H. Binder, A. Prasse, J. Müller-Quernheim, 2015, PloS one.

Dealing with prognostic signature instability: a strategy illustrated for cardiovascular events in patients with end-stage renal disease

T. Kurz, J. Timmer, H. Binder, 2016, BMC Medical Genomics.

Interpretable generative deep learning: an illustration with single cell gene expression data

H. Binder, M. Treppner, M. Hess, 2022, Human Genetics.

PCF11 links alternative polyadenylation to formation and spontaneous regression of neuroblastoma

F. Westermann, H. Binder, B. Tian, 2018, bioRxiv.

Transcriptome 3′end organization by PCF11 links alternative polyadenylation to formation and neuronal differentiation of neuroblastoma

F. Westermann, H. Binder, B. Tian, 2018, Nature Communications.

Translating bioinformatics in oncology: Guilty by profiling meta-analysis and identification of KIF18B and CDCA3 as novel driver genes in liver carcinogenesis

X. Wang, S. Thorgeirsson, H. Binder, 2013 .

Interactive and Reproducible Workflows for Exploring and Modeling RNA‐seq Data with pcaExplorer, Ideal, and GeneTonic

H. Binder, Federico Marini, Konstantin Strauch, 2022, Current protocols.

Transcriptome Analysis in Patients with Progressive Coronary Artery Disease: Identification of Differential Gene Expression in Peripheral Blood

T. Kurz, H. Binder, F. Neumann, 2013, Journal of Cardiovascular Translational Research.

The performance of deep generative models for learning joint embeddings of single-cell multi-omics data

H. Binder, C. Kreutz, Maren Hackenberg, 2022, bioRxiv.

Genetic Cell Ablation Reve als Clusters of Local Self-Renewing Microglia in the Mammalian Central Nervous System Graphical

Steffen Jung, H. Binder, F. Zipp, 2022 .

Multivariable model-building with continuous covariates : 2 . Comparison between splines and fractional polynomials

P. Royston, W. Sauerbrei, H. Binder, 2011 .

Adding local components to global functions for continuous covariates in multivariable regression modeling

W. Sauerbrei, H. Binder, 2010, Statistics in medicine.

Interleukin-1 promotes autoimmune neuroinflammation by suppressing endothelial heme oxygenase-1 at the blood–brain barrier

H. Binder, A. Waisman, M. Schwaninger, 2020, Acta Neuropathologica.

minPtest: a resampling based gene region-level testing procedure for genetic case-control studies

H. Binder, A. Nieters, S. Hieke, 2013, Computational Statistics.

Can matching improve the performance of boosting for identifying important genes in observational studies?

H. Binder, M. Schumacher, S. Stampf, 2012, Computational Statistics.

Comparison of time and dose dependent gene expression and affected pathways in primary human fibroblasts after exposure to ionizing radiation

H. Binder, M. Blettner, T. Hankeln, 2020, Molecular medicine.

pcaExplorer: an R/Bioconductor package for interacting with RNA-seq principal components

H. Binder, F. Marini, 2018, bioRxiv.

Combining techniques for screening and evaluating interaction terms on high-dimensional time-to-event data

H. Binder, M. Sariyar, I. Hoffmann, 2014, BMC Bioinformatics.

Stratified neural networks in a time-to-event setting

H. Binder, M. Hess, Fabrizio Kuruc, 2021, bioRxiv.

Deep dynamic modeling with just two time points: Can we still allow for individual trajectories?

H. Binder, Thorsten Schmidt, Maren Hackenberg, 2020, Biometrical journal. Biometrische Zeitschrift.

Comments on “Identifying inconsistency in network meta‐analysis: Is the net heat plot a reliable method?”

G. Rücker, H. Binder, J. König, 2021, Statistics in medicine.

A graphical tool for locating inconsistency in network meta-analyses

Harald Binder, Ulrike Krahn, Jochem König, 2013, BMC Medical Research Methodology.

Prognostic Factor Studies

Guido Schwarzer, Harald Binder, Willi Sauerbrei, 2012 .

The Evolution of Boosting Algorithms

A Mayr, H Binder, O Gefeller, 2014, Methods of Information in Medicine.

Dealing with prognostic signature instability: a strategy illustrated for cardiovascular events in patients with end-stage renal disease

T. Kurz, J. Timmer, H. Binder, 2016, BMC Medical Genomics.

Exploring generative deep learning for omics data using log-linear models

Maren Hackenberg, Harald Binder, Moritz Hess, 2020, Bioinform..

Synthetic single cell RNA sequencing data from small pilot studies using deep generative models

H. Binder, T. Vogel, S. Lenz, 2021, Scientific Reports.

A meta-analysis of 120 246 individuals identifies 18 new loci for fibrinogen concentration.

Lorna M. Lopez, Min A. Jhun, R. Marioni, 2016, Human molecular genetics.

Genetic Cell Ablation Reveals Clusters of Local Self-Renewing Microglia in the Mammalian Central Nervous System.

Frauke Zipp, Werner Müller, Harald Binder, 2015, Immunity.

Designing Single Cell RNA-Sequencing Experiments for Learning Latent Representations

H. Binder, A. Köttgen, S. Haug, 2022, bioRxiv.

Synthetic observations from deep generative models and binary omics data with limited sample size.

Harald Binder, Moritz Hess, Stefan Lenz, 2020, Briefings in bioinformatics.

Synthetic observations from deep generative models and binary omics data with limited sample size

Harald Binder, Moritz Hess, Stefan Lenz, 2020, bioRxiv.

Generating Synthetic Single-Cell RNA-Sequencing Data from Small Pilot Studies using Deep Learning

Harald Binder, Martin Treppner, Moritz Hess, 2020 .

Making many out of few: deep generative models for single-cell RNA-sequencing data

Harald Binder, Martin Treppner, Moritz Hess, 2020, bioRxiv.

Netboost: Boosting-Supported Network Analysis Improves High-Dimensional Omics Prediction in Acute Myeloid Leukemia and Huntington’s Disease

C. Plass, H. Binder, L. Bullinger, 2019, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Novel circulating microRNA signature as a potential non‐invasive multi‐marker test in ER‐positive early‐stage breast cancer: A case control study

H. Binder, H. Ditzel, S. Cold, 2014, Molecular oncology.

Transcriptome 3′end organization by PCF11 links alternative polyadenylation to formation and neuronal differentiation of neuroblastoma

F. Westermann, H. Binder, B. Tian, 2018, Nature Communications.

Stability Investigations of Multivariable Regression Models Derived from Low- and High-Dimensional Data

Anne-Laure Boulesteix, Harald Binder, Willi Sauerbrei, 2011, Journal of biopharmaceutical statistics.

Boosting for high-dimensional time-to-event data with competing risks

Harald Binder, Martin Schumacher, Jan Beyersmann, 2009, Bioinform..

Promoter-proximal pausing mediated by the exon junction complex regulates splicing

H. Binder, Jean-Yves Roignant, Junaid Akhtar, 2019, Nature Communications.

The exon junction complex regulates the release and phosphorylation of paused RNA polymerase II

H. Binder, Jean-Yves Roignant, Junaid Akhtar, 2018, bioRxiv.

Distributed multivariable modeling for signature development under data protection constraints pdf

Harald Binder, Stefan Lenz, Daniela Zöller, 2018, ArXiv.

ideal: an R/Bioconductor package for interactive differential expression analysis

Federico Marini, Harald Binder, Jan Linke, 2020, BMC Bioinformatics.

BAL Cell Gene Expression Is Indicative of Outcome and Airway Basal Cell Involvement in Idiopathic Pulmonary Fibrosis

G. Kayser, H. Binder, N. Krug, 2019, American journal of respiratory and critical care medicine.

Identification of a 17-protein signature in the serum of lung cancer patients.

H. Binder, M. Schumacher, U. Martens, 2010, Oncology reports.

Graph based fusion of miRNA and mRNA expression data improves clinical outcome prediction in prostate cancer

Tim Beißbarth, Holger Sültmann, Harald Binder, 2011, BMC Bioinformatics.

Incorporating pathway information into boosting estimation of high-dimensional risk prediction models

Harald Binder, Martin Schumacher, H. Binder, 2009, BMC Bioinformatics.

Assessment of survival prediction models based on microarray data

Harald Binder, Martin Schumacher, Thomas Gerds, 2007, Bioinform..

Single-cell transcriptomic resolution of stem cells and their developmental trajectories in the hippocampus reveals epigenetic control of cell state perseverance

Michael B. Stadler, H. Binder, T. Vogel, 2021, bioRxiv.

Cerebral ischemia-induced genes are increased in acute schizophrenia: an opportunity for clinical translation of genomic research findings

H. Binder, H. Moises, M. Hess, 2017, bioRxiv.

Boosting ridge regression

Gerhard Tutz, Harald Binder, G. Tutz, 2007, Comput. Stat. Data Anal..

Tutz , Binder : Boosting Ridge Regression

G. Tutz, H. Binder, 2007 .

Standalone Smartphone Cognitive Behavioral Therapy–Based Ecological Momentary Interventions to Increase Mental Health: Narrative Review

H. Walter, H. Binder, R. Kalisch, 2020, JMIR mHealth and uHealth.

Comparison of HapMap and 1000 Genomes Reference Panels in a Large-Scale Genome-Wide Association Study

Jie Huang, Uwe Völker, Ming-Huei Chen, 2017, PloS one.

Genetic signatures shared in embryonic liver development and liver cancer define prognostically relevant subgroups in HCC

Harald Binder, Thorsten Maass, Markus Krupp, 2012, Molecular Cancer.

Gene expression patterns underlying parasite‐induced alterations in host behaviour and life history

H. Binder, S. Foitzik, B. Feldmeyer, 2016, Molecular ecology.

Localized classification

Gerhard Tutz, Harald Binder, G. Tutz, 2005, Stat. Comput..

Epigenetic modifications precede molecular alterations and drive human hepatocarcinogenesis

S. Thorgeirsson, H. Binder, M. Odenthal, 2021, JCI insight.

ERK3/MAPK6 controls IL-8 production and chemotaxis

H. Binder, H. Schild, K. Rajalingam, 2020, eLife.

Regularized regression when covariates are linked on a network: the 3CoSE algorithm

H. Binder, Matthias Weber, M. Schumacher, 2021, Journal of applied statistics.

Regularized Regression Incorporating Network Information: Simultaneous Estimation of Covariate Coefficients and Connection Signs

Harald Binder, Martin Schumacher, H. Binder, 2014 .

Sparse regression techniques in low-dimensional survival data settings

Harald Binder, Martin Schumacher, Christine Porzelius, 2010, Stat. Comput..

A general, prediction error‐based criterion for selecting model complexity for high‐dimensional survival models

Harald Binder, Martin Schumacher, Christine Porzelius, 2010, Statistics in medicine.

Allowing for mandatory covariates in boosting estimation of sparse high-dimensional survival models

Harald Binder, Martin Schumacher, H. Binder, 2008, BMC Bioinformatics.

Large platelets but not putative endothelial progenitor cells are associated with low strut coverage after drug-eluting stent implantation.

H. Binder, F. Neumann, M. Amann, 2015, International journal of cardiology.

Feasibility of sample size calculation for RNA‐seq studies

Harald Binder, Alicia Poplawski, H. Binder, 2017, Briefings Bioinform..

Sequential Learning of Regression Models by Penalized Estimation

H. Binder, W. V. van Wieringen, W. N. Wieringen, 2022, J. Comput. Graph. Stat..

Transfer learning of regression models from a sequence of datasets by penalized estimation.

Harald Binder, Wessel N. van Wieringen, H. Binder, 2020, 2007.02117.

On the necessity and design of studies comparing statistical methods

Anne-Laure Boulesteix, Harald Binder, Willi Sauerbrei, 2018, Biometrical journal. Biometrische Zeitschrift.

Integrating multiple molecular sources into a clinical risk prediction signature by extracting complementary information

Richard F. Schlenl, H. Binder, L. Bullinger, 2016, BMC Bioinformatics.

Bioinformatics Applications Note Parallelized Prediction Error Estimation for Evaluation of High-dimensional Models

Harald Binder, Martin Schumacher, Christine Porzelius, 2022 .

Translating bioinformatics in oncology: guilt-by-profiling analysis and identification of KIF18B and CDCA3 as novel driver genes in carcinogenesis

Harald Binder, Peter Scholz, Andreas Teufel, 2015, Bioinform..

ideal: an R/Bioconductor package for interactive differential expression analysis

Federico Marini, Harald Binder, Jan Linke, 2020, BMC Bioinformatics.

Increasing the usefulness of additive spline models by knot removal

Harald Binder, Willi Sauerbrei, W. Sauerbrei, 2008, Comput. Stat. Data Anal..

A meta-analysis of 120 246 individuals identifies 18 new loci for fibrinogen concentration.

Peter K. Joshi, Lorna M. Lopez, Min A. Jhun, 2016, Human molecular genetics.

Identifying Prognostic SNPs in Clinical Cohorts: Complementing Univariate Analyses by Resampling and Multivariable Modeling

Axel Benner, Harald Binder, Martin Schumacher, 2016, PloS one.

A multivariable approach for risk markers from pooled molecular data with only partial overlap

Harald Binder, Alexandra Nieters, Martin Schumacher, 2019, BMC Medical Genetics.

Visualizing inconsistency in network meta-analysis by independent path decomposition

Harald Binder, Ulrike Krahn, Jochem König, 2014, BMC Medical Research Methodology.

Molecular cause and functional impact of altered synaptic lipid signaling due to a prg‐1 gene SNP

Harald Binder, Jan Baumgart, Peter Nürnberg, 2015, EMBO molecular medicine.

Uncontrolled Diabetes Mellitus Has No Major Influence on the Platelet Transcriptome

H. Binder, F. Neumann, B. Grüning, 2018, BioMed research international.

DOT1L activity affects cell lineage progression in the developing brain by controlling metabolic programs

H. Binder, T. Vogel, A. Cheffer, 2022, bioRxiv.

Visualizing the flow of evidence in network meta‐analysis and characterizing mixed treatment comparisons

Harald Binder, Ulrike Krahn, Jochem König, 2013, Statistics in medicine.

Development of Applications for Interactive and Reproducible Research: a Case Study

Harald Binder, Federico Marini, H. Binder, 2016 .

State of the art in selection of variables and functional forms in multivariable analysis—outstanding issues

Willi Sauerbrei, Geraldine Rauch, Harald Binder, 2019, Diagnostic and Prognostic Research.

The immune contexture of hepatocellular carcinoma predicts clinical outcome

H. Binder, D. Schuppan, P. Galle, 2018, Scientific Reports.

Time-to-first-event versus recurrent-event analysis: points to consider for selecting a meaningful analysis strategy in clinical trials with composite endpoints

H. Binder, A. Bayés‐Genís, M. Kieser, 2018, Clinical Research in Cardiology.

Machine learning for identifying relevant publications in updates of systematic reviews of diagnostic test studies

H. Binder, T. Lange, G. Schwarzer, 2020, medRxiv.

Quantifying the predictive accuracy of time‐to‐event models in the presence of competing risks

Harald Binder, Martin Schumacher, Jan Beyersmann, 2011, Biometrical journal. Biometrische Zeitschrift.

Comparison between splines and fractional polynomials for multivariable model building with continuous covariates: a simulation study with continuous response

Patrick Royston, Harald Binder, Willi Sauerbrei, 2013, Statistics in medicine.

Multivariable model-building with continuous covariates : 1 . Performance measures and simulation design

Patrick Royston, Harald Binder, Willi Sauerbrei, 2011 .

A comparison of methods for the fitting of generalized additive models

Gerhard Tutz, Harald Binder, G. Tutz, 2008, Stat. Comput..

Recovery of original individual person data (IPD) inferences from empirical IPD summaries only: Applications to distributed computing under disclosure constraints

Harald Binder, Martin Schumacher, Federico Bonofiglio, 2020, Statistics in medicine.

Micro-array profiling exhibits remarkable intra-individual stability of human platelet micro-RNA

H. Binder, B. Fiebich, D. Trenk, 2012, Thrombosis and Haemostasis.

Statistical analysis of high-dimensional biomedical data: a gentle introduction to analytical goals, common approaches and challenges

A. Boulesteix, W. Sauerbrei, H. Binder, 2023, BMC Medicine.

Pitfalls of hypothesis tests and model selection on bootstrap samples: Causes and consequences in biometrical applications

Anne-Laure Boulesteix, Harald Binder, Silke Janitza, 2016, Biometrical journal. Biometrische Zeitschrift.

Deep learning and differential equations for modeling changes in individual‐level latent dynamics between observation periods

H. Binder, R. Kalisch, G. Köber, 2022, Biometrical journal. Biometrische Zeitschrift.

Individualizing deep dynamic models for psychological resilience data

Haakon G. Engen, G. KoÌber, S. Pooseh, 2020, Scientific Reports.

DOT1L activity affects neural stem cell division mode and reduces differentiation and ASNS expression

H. Binder, T. Vogel, A. Cheffer, 2023, EMBO reports.

DOT1L activity affects cell lineage progression in the developing brain by controlling metabolic programs

H. Binder, T. Vogel, A. Cheffer, 2022, bioRxiv.

Adapting deep generative approaches for getting synthetic data with realistic marginal distributions pdf

Federico Bonofiglio, Harald Binder, Kiana Farhadyar, 2021, ArXiv.

Extending Statistical Boosting

H. Binder, O. Gefeller, M. Schmid, 2014, Methods of Information in Medicine.

Controlled type II diabetes mellitus has no major influence on platelet micro-RNA expression

Harald Binder, Asit Kumar, H. Binder, 2013, Thrombosis and Haemostasis.

Encoding Medical Experiments in Jupyter Notebooks

Harald Binder, Kiana Farhadyar, Jochen Knaus, 2021 .

Alterations in Circulating miRNA Levels following Early-Stage Estrogen Receptor-Positive Breast Cancer Resection in Post-Menopausal Women

H. Binder, H. Ditzel, A. Knoop, 2014, PloS one.

Gene expression variability in long-term survivors of childhood cancer and cancer-free controls in response to ionizing irradiation

H. Binder, M. Blettner, R. Foraita, 2023, Molecular Medicine.

Easier parallel computing in R with snowfall and sfCluster

Guido Schwarzer, Harald Binder, Christine Porzelius, 2009, R J..

pcaExplorer: an R/Bioconductor package for interacting with RNA-seq principal components

Federico Marini, Harald Binder, H. Binder, 2018, BMC Bioinformatics.

Simulating recurrent event data with hazard functions defined on a total time scale

Harald Binder, Antje Jahn-Eimermacher, Katharina Ingel, 2015, BMC Medical Research Methodology.

Integrating multiple molecular sources into a clinical risk prediction signature by extracting complementary information

Axel Benner, Harald Binder, Martin Schumacher, 2016, BMC Bioinformatics.

Systematically evaluating interfaces for RNA-seq analysis from a life scientist perspective

Federico Marini, Harald Binder, Johanna Mazur, 2016, Briefings Bioinform..

Partitioned Learning of Deep Boltzmann Machines for SNP Data

Harald Binder, Stefan Lenz, Lars Bullinger, 2016, bioRxiv.

Comment on "network-constrained regularization and variable selection for analysis of genomic data"

H. Binder, M. Schumacher, 2008, Bioinform..

Micro-array profiling exhibits remarkable intra-individual stability of human platelet micro-RNA

H. Binder, B. Fiebich, D. Trenk, 2012, Thrombosis and Haemostasis.

Distributed Multivariate Regression Modeling For Selecting Biomarkers Under Data Protection Constraints

H. Binder, Daniel Zoller, 2018, 1803.00422.

Tailoring sparse multivariable regression techniques for prognostic single‐nucleotide polymorphism signatures

M Schumacher, A Benner, H Binder, 2013, Statistics in medicine.

What subject matter questions motivate the use of machine learning approaches compared to statistical models for probability prediction?

H. Binder, 2014, Biometrical journal. Biometrische Zeitschrift.

A general, prediction error‐based criterion for selecting model complexity for high‐dimensional survival models

H. Binder, M. Schumacher, C. Porzelius, 2010, Statistics in medicine.

Parallelized prediction error estimation for evaluation of high-dimensional models

H. Binder, M. Schumacher, C. Porzelius, 2009, Bioinform..

Statistical Applications in Genetics and Molecular Biology Cluster-Localized Sparse Logistic Regression for SNP Data

Holger Schwender, Harald Binder, Martin Schumacher, 2012 .

Stagewise pseudo‐value regression for time‐varying effects on the cumulative incidence

Daniela Zöller, Irene Schmidtmann, Arndt Weinmann, 2016, Statistics in medicine.

Comparison between splines and fractional polynomials for multivariable model building with continuous covariates: a simulation study with continuous response

P. Royston, W. Sauerbrei, H. Binder, 2013, Statistics in medicine.

Grid and Cloud Computing Methods in Biomedical Research

H Binder, H. Binder, M. Schmid, 2013, Methods of Information in Medicine.

Can matching improve the performance of boosting for identifying important genes in observational studies?

Harald Binder, Martin Schumacher, Veronika Reiser, 2012, Computational Statistics.

Unsupervised deep learning on biomedical data with BoltzmannMachines.jl

Harald Binder, Stefan Lenz, Moritz Hess, 2019, bioRxiv.

Deep generative models in DataSHIELD pdf

Harald Binder, Stefan Lenz, H. Binder, 2020, BMC Medical Research Methodology.

Combining techniques for screening and evaluating interaction terms on high-dimensional time-to-event data

Murat Sariyar, Harald Binder, Isabell Hoffmann, 2014, BMC Bioinformatics.

Network-Constrained Covariate Coefficient and Connection Sign Estimation

H. Binder, M. Schumacher, Matthias Weber, 2018, SSRN Electronic Journal.