A. Boulesteix

A. Boulesteix, C. Hübener, A. Flemmer, 2020, The journal of maternal-fetal & neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians.

Iterative Reconstruction of High-Dimensional Gaussian Graphical Models Based on a New Method to Estimate Partial Correlations under Constraints

A. Boulesteix, Andreas Bender, V. Guillemot, 2013, PloS one.

On stability issues in deriving multivariable regression models

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

Statistical learning approaches in the genetic epidemiology of complex diseases

Marvin N. Wright, A. Boulesteix, I. König, 2019, Human Genetics.

Efficient Computation of Unconditional Error Rate Estimators for Learning Algorithms and an Application to a Biomedical Data

A. Boulesteix, 2014 .

Letter to the Editor: On the term ‘interaction’ and related phrases in the literature on Random Forests

Carolin Strobl, Anne-Laure Boulesteix, Silke Janitza, 2014, Briefings Bioinform..

Mid-term outcomes of patients with PCI prior to CABG in comparison to patients with primary CABG

A. Boulesteix, B. Reichart, H. Mair, 2010, Vascular health and risk management.

Functional genomics: tools for improving farm animal health and welfare.

A. Boulesteix, E. Wolf, S. Bauersachs, 2005, Revue scientifique et technique.

Torsten Hothorn Bias in Random Forest Variable Importance Measures : Illustrations , Sources and a Solution Paper

A. Boulesteix, T. Hothorn, A. Zeileis, 2016 .

Over-optimism in bioinformatics research

Anne-Laure Boulesteix, A. Boulesteix, 2010, Bioinform..

Differential expression of the chemokines GRO-2, GRO-3, and interleukin-8 in colon cancer and their impact on metastatic disease and survival

A. Boulesteix, M. Maak, J. Siewert, 2010, International Journal of Colorectal Disease.

Breath isoprene concentrations in persons undergoing general anesthesia and in healthy volunteers

A. Boulesteix, G. Schelling, F. Weis, 2012, Journal of breath research.

Introduction to statistical simulations in health research

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

Use of pre-transformation to cope with outlying values in important candidate genes

A. Boulesteix, G. Vincent, S. Willi, 2010 .

Identification of gene association networks of the cellular radiation response from time-course transcriptomic data

A. Boulesteix, R. Hickel, Eidesstattliche Versicherung, 2017 .

Extracorporeal Life Support in Cardiogenic Shock Complicating Acute Myocardial Infarction.

A. Boulesteix, J. Hausleiter, S. Peterss, 2019, Journal of the American College of Cardiology.

Over-optimism in unsupervised microbiome analysis: Insights from network learning and clustering

Christian L. Müller, A. Boulesteix, Theresa Ullmann, 2022, bioRxiv.

Gene expression Over-optimism in bioinformatics research

A. Boulesteix, 2010 .

The Radiation Induced Migration of Human Malignant Glioma Cells can be Blocked by Inhibition of the EGFR Downstream Pathways

A. Boulesteix, G. Piontek, J. Schlegel, 2012 .

On the choice and influence of the number of boosting steps for high-dimensional linear Cox-models

Riccardo De Bin, A. Boulesteix, H. Seibold, 2016, Computational Statistics.

Expression of STK15, EGFR, p53 and p16INK4A by Squamous Cell Carcinoma (SCC) of the Nasal Cavity and the Paranasal Sinuses

A. Boulesteix, G. Piontek, R. Reiter, 2012 .

COMPANION: development of a patient-centred complexity and casemix classification for adult palliative care patients based on needs and resource use – a protocol for a cross-sectional multi-centre study

A. Boulesteix, C. Bausewein, R. Leidl, 2022, BMC Palliative Care.

Immune function testing in sepsis patients receiving sodium selenite.

A. Boulesteix, J. Briegel, A. Choukér, 2019, Journal of critical care.

Interleukin-22 is elevated in lavage from patients with lung cancer and other pulmonary diseases

A. Boulesteix, M. Edelmann, F. Gamarra, 2016, BMC Cancer.

Over-optimism in unsupervised microbiome analysis: Insights from network learning and clustering

Christian L. Müller, A. Boulesteix, Theresa Ullmann, 2022, bioRxiv.

The multiplicity of analysis strategies jeopardizes replicability: lessons learned across disciplines

Felix D. Schönbrodt, A. Boulesteix, Ralf Elsas, 2020, Royal Society Open Science.

Critical appraisal of artificial intelligence-based prediction models for cardiovascular disease

Spiros C. Denaxas, A. Boulesteix, B. van Calster, 2022, European heart journal.

Comparing supervised machine learning algorithms for the prediction of partial arterial pressure of oxygen during craniotomy

A. Boulesteix, L. C. Hinske, B. Geisler, 2022, medRxiv.

Statisticians, roll up your sleeves! There's a crisis to be solved

A. Boulesteix, H. Seibold, Sabine Hoffmann, 2020, Significance.

Gram-negative and -positive bacteria differentiation in blood culture samples by headspace volatile compound analysis

A. Boulesteix, Silke Janitza, G. Schelling, 2016, Journal of Biological Research-Thessaloniki.

Phases of methodological research in biostatistics-Building the evidence base for new methods.

A. Boulesteix, T. Morris, Georg Heinze, 2022, Biometrical journal. Biometrische Zeitschrift.

On the asymptotic behaviour of the variance estimator of a U-statistic

A. Boulesteix, R. Hornung, Mathias Fuchs, 2020 .

Cell Carcinoma (SCC) of the Nasal Cavity and the Paranasal

A. Boulesteix, G. Piontek, R. Reiter, 2012 .

Centrosome abnormalities in head and neck squamous cell carcinoma (HNSCC)

A. Boulesteix, S. Rauser, H. Höfler, 2009, Acta oto-laryngologica.

Effective methods to enhance medical students’ cardioversion and transcutaneous cardiac pacing skills retention - a prospective controlled study

A. Boulesteix, S. Harendza, C. Kowalski, 2022, BMC medical education.

Mediation analysis reveals common mechanisms of RUNX1 point mutations and RUNX1/RUNX1T1 fusions influencing survival of patients with acute myeloid leukemia

A. Boulesteix, W. Hiddemann, K. Metzeler, 2018, Scientific Reports.

The residual‐based predictiveness curve: A visual tool to assess the performance of prediction models

Bernd Bischl, Anne-Laure Boulesteix, Matthias Schmid, 2016, Biometrics.

Improved Outcome Prediction Across Data Sources Through Robust Parameter Tuning

A. Boulesteix, R. Hornung, Bernd Bischl, 2020, Journal of Classification.

Homografts in aortic position: does blood group incompatibility have an impact on patient outcomes?

A. Boulesteix, B. Reichart, G. Santarpino, 2013, Interactive cardiovascular and thoracic surgery.

Planning preclinical confirmatory multicenter trials to strengthen translation from basic to clinical research – a multi-stakeholder workshop report

A. Boulesteix, B. Voelkl, T. Friede, 2022, Translational Medicine Communications.

Categorical variables with many categories are preferentially selected in bootstrap‐based model selection procedures for multivariable regression models

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

Critical review of reporting of the data analysis step in metabolomics

Elizabeth C. Considine, A. Boulesteix, A. Khashan, 2017, Metabolomics.

Aprotinin and anaphylaxis: analysis of 12,403 exposures to aprotinin in cardiac surgery.

A. Boulesteix, W. Dietrich, R. Busley, 2007, The Annals of thoracic surgery.

Effects of Aprotinin Dosage on Renal Function: An Analysis of 8,548 Cardiac Surgical Patients Treated with Different Dosages of Aprotinin

A. Boulesteix, W. Dietrich, R. Busley, 2008, Anesthesiology.

A note on between-group PCA

Anne-Laure Boulesteix, A. Boulesteix, 2004 .

Unbiased split selection for classification trees based on the Gini Index

Carolin Strobl, Anne-Laure Boulesteix, Thomas Augustin, 2007, Comput. Stat. Data Anal..

BMC Bioinformatics BioMed Central Methodology article Conditional variable importance for random forests

Achim Zeileis, Carolin Strobl, Anne-Laure Boulesteix, 2008 .

Detection of influential points as a byproduct of resampling-based variable selection procedures

Anne-Laure Boulesteix, Willi Sauerbrei, Riccardo De Bin, 2017, Comput. Stat. Data Anal..

An AUC-based permutation variable importance measure for random forests

Carolin Strobl, Anne-Laure Boulesteix, Silke Janitza, 2013, BMC Bioinformatics.

A U-statistic estimator for the variance of resampling-based error estimators

Roman Hornung, Anne-Laure Boulesteix, Riccardo De Bin, 2013, 1310.8203.

CMA – a comprehensive Bioconductor package for supervised classification with high dimensional data

Anne-Laure Boulesteix, Martin Daumer, Martin Slawski, 2008, BMC Bioinformatics.

Gender mismatch in allograft aortic valve surgery.

A. Boulesteix, C. Schmitz, F. Vogt, 2015, Interactive cardiovascular and thoracic surgery.

Methylene Blue halves the long-term recurrence rate in acute pilonidal sinus disease

A. Boulesteix, J. Kristiansen, A. Novotny, 2008, International Journal of Colorectal Disease.

Time and rate of sinus formation in pilonidal sinus disease

A. Boulesteix, J. Friederichs, D. Doll, 2008, International Journal of Colorectal Disease.

Overview of random forest methodology and practical guidance with emphasis on computational biology and bioinformatics

Anne-Laure Boulesteix, Silke Janitza, Jochen Kruppa, 2012, WIREs Data Mining Knowl. Discov..

Influence of diatoms on copepod reproduction. II. Uncorrelated effects of diatom-derived alpha,beta,gamma,delta-unsaturated aldehydes and polyunsaturated fatty acids on Calanus helgolandicus in the field

A. Boulesteix, Thomas Wichard, G. Pohnert, 2008 .

Bias in random forest variable importance measures: Illustrations, sources and a solution

Achim Zeileis, Carolin Strobl, Torsten Hothorn, 2007, BMC Bioinformatics.

Inhibition of radiation induced migration of human head and neck squamous cell carcinoma cells by blocking of EGF receptor pathways

A. Boulesteix, G. Piontek, S. Pigorsch, 2011, BMC Cancer.

Partial least squares: a versatile tool for the analysis of high-dimensional genomic data

Anne-Laure Boulesteix, Korbinian Strimmer, A. Boulesteix, 2006, Briefings Bioinform..

Essential guidelines for computational method benchmarking

A. Boulesteix, Y. Saeys, M. Robinson, 2018, Genome biology.

Large-scale benchmark study of survival prediction methods using multi-omics data

Moritz Herrmann, Philipp Probst, Roman Hornung, 2020, Briefings Bioinform..

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.

A computationally fast variable importance test for random forests for high-dimensional data

Anne-Laure Boulesteix, Silke Janitza, Ender Celik, 2015, Adv. Data Anal. Classif..

A computationally fast variable importance test for random forests for high-dimensional data

A. Boulesteix, Silke Janitza, Ender Celik, 2016, Advances in Data Analysis and Classification.

Improved prediction of complex diseases by common genetic markers: state of the art and further perspectives

Anne-Laure Boulesteix, Jens Brauer, Arndt Wilcke, 2016, Human Genetics.

Microarray-based prediction of tumor response to neoadjuvant radiochemotherapy of patients with locally advanced rectal cancer.

Anne-Laure Boulesteix, Karen Becker, Robert Rosenberg, 2008, Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association.

Added predictive value of high-throughput molecular data to clinical data and its validation

Anne-Laure Boulesteix, Willi Sauerbrei, A. Boulesteix, 2011, Briefings Bioinform..

A CART-based approach to discover emerging patterns in microarray data

Gerhard Tutz, Anne-Laure Boulesteix, Korbinian Strimmer, 2003, Bioinform..

NetCoMi: network construction and comparison for microbiome data in R

Christian L. Müller, Anne-Laure Boulesteix, Stefanie Peschel, 2020, bioRxiv.

Combining clinical and molecular data in regression prediction models: insights from a simulation study

Anne-Laure Boulesteix, Axel Benner, Willi Sauerbrei, 2019, Briefings Bioinform..

A plea for taking all available clinical information into account when assessing the predictive value of omics data

Anne-Laure Boulesteix, Willi Sauerbrei, Riccardo De Bin, 2019, BMC medical research methodology.

On Fishing for Significance and Statistician’s Degree of Freedom in the Era of Big Molecular Data

Roman Hornung, Anne-Laure Boulesteix, Willi Sauerbrei, 2017 .

Cross-study validation for the assessment of prediction algorithms

Anne-Laure Boulesteix, Lorenzo Trippa, Curtis Huttenhower, 2014, Bioinform..

Live music reduces stress levels in very low‐birthweight infants

A. Boulesteix, A. Schulze, M. Vogeser, 2015, Acta paediatrica.

On the optimistic performance evaluation of newly introduced bioinformatic methods

A. Boulesteix, A. Hapfelmeier, Rory Wilson, 2021, Genome biology.

AUC-RF: A New Strategy for Genomic Profiling with Random Forest

Anne-Laure Boulesteix, M. L. Calle, Victor Urrea, 2011, Human Heredity.

Essential guidelines for computational method benchmarking

Yvan Saeys, Anne-Laure Boulesteix, Robrecht Cannoodt, 2018, Genome Biology.

Gram-negative and -positive bacteria differentiation in blood culture samples by headspace volatile compound analysis

A. Boulesteix, Silke Janitza, G. Schelling, 2016, Journal of Biological Research-Thessaloniki.

On the choice and influence of the number of boosting steps for high-dimensional linear Cox-models

Anne-Laure Boulesteix, Christoph Bernau, Riccardo De Bin, 2018, Comput. Stat..

Survival prediction using gene expression data: A review and comparison

Anne-Laure Boulesteix, Wessel N. van Wieringen, David Kun, 2009, Comput. Stat. Data Anal..

Machine learning versus statistical modeling

Anne-Laure Boulesteix, Matthias Schmid, A. Boulesteix, 2014, Biometrical journal. Biometrische Zeitschrift.

Methylation of Tumor-Related Genes in Neoadjuvant-Treated Gastric Cancer: Relation to Therapy Response and Clinicopathologic and Molecular Features

A. Boulesteix, H. Höfler, F. Lordick, 2007, Clinical Cancer Research.

Random forest for ordinal responses: Prediction and variable selection

Gerhard Tutz, Anne-Laure Boulesteix, Silke Janitza, 2016, Comput. Stat. Data Anal..

Random forest Gini importance favours SNPs with large minor allele frequency: impact, sources and recommendations

Carolin Strobl, Andreas Bender, Anne-Laure Boulesteix, 2012, Briefings Bioinform..

An eight-gene expression signature for the prediction of survival and time to treatment in chronic lymphocytic leukemia

Anne-Laure Boulesteix, Ulrich Mansmann, Klaus H. Metzeler, 2011, Leukemia.

Stability and aggregation of ranked gene lists

Anne-Laure Boulesteix, Martin Slawski, A. Boulesteix, 2009, Briefings Bioinform..

Ten Simple Rules for Reducing Overoptimistic Reporting in Methodological Computational Research

Anne-Laure Boulesteix, A. Boulesteix, 2015, PLoS Comput. Biol..

Combining location-and-scale batch effect adjustment with data cleaning by latent factor adjustment

A. Boulesteix, R. Hornung, D. Causeur, 2016, BMC Bioinformatics.

Prediction approaches for partly missing multi-omics covariate data: A literature review and an empirical comparison study

A. Boulesteix, R. Hornung, Frederik Ludwigs, 2023, ArXiv.

Priority-Lasso: a simple hierarchical approach to the prediction of clinical outcome using multi-omics data

A. Boulesteix, R. Hornung, T. Herold, 2018, BMC Bioinformatics.

On the necessity and design of studies comparing statistical methods

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

Towards evidence-based computational statistics: lessons from clinical research on the role and design of real-data benchmark studies

Rory Wilson, Anne-Laure Boulesteix, Alexander Hapfelmeier, 2017, BMC Medical Research Methodology.

Improving cross‐study prediction through addon batch effect adjustment or addon normalization

David Causeur, Roman Hornung, Anne-Laure Boulesteix, 2016, Bioinform..

MRI-based contrast clearance analysis shows high differentiation accuracy between radiation-induced reactions and progressive disease after cranial radiotherapy

A. Boulesteix, N. Albert, C. Belka, 2022, ESMO open.

Independent validation of a new reirradiation risk score (RRRS) for glioma patients predicting post-recurrence survival: A multicenter DKTK/ROG analysis.

A. Boulesteix, V. Budach, J. Debus, 2018, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

Sampling uncertainty versus method uncertainty: A general framework with applications to omics biomarker selection

Anne-Laure Boulesteix, Simon Klau, Marie-Laure Martin-Magniette, 2019, Biometrical journal. Biometrische Zeitschrift.

Priority-Lasso: a simple hierarchical approach to the prediction of clinical outcome using multi-omics data

Roman Hornung, Vindi Jurinovic, Anne-Laure Boulesteix, 2018, BMC Bioinformatics.

Mediation analysis reveals common mechanisms of RUNX1 point mutations and RUNX1/RUNX1T1 fusions influencing survival of patients with acute myeloid leukemia

A. Boulesteix, W. Hiddemann, K. Metzeler, 2018, Scientific Reports.

Random forest versus logistic regression: a large-scale benchmark experiment

Philipp Probst, Anne-Laure Boulesteix, Raphaël Couronné, 2018, BMC Bioinformatics.

To tune or not to tune the number of trees in random forest?

Philipp Probst, Anne-Laure Boulesteix, A. Boulesteix, 2017, J. Mach. Learn. Res..

A measure of the impact of CV incompleteness on prediction error estimation with application to PCA and normalization

Rory Wilson, Roman Hornung, Caroline Truntzer, 2015, BMC Medical Research Methodology.

Complexity Selection with Cross-validation for Lasso and Sparse Partial Least Squares Using High-Dimensional Data

Anne-Laure Boulesteix, Christoph Bernau, Adrian Richter, 2013, Algorithms from and for Nature and Life.

Use of pretransformation to cope with extreme values in important candidate features

Anne-Laure Boulesteix, Willi Sauerbrei, Vincent Guillemot, 2011, Biometrical journal. Biometrische Zeitschrift.

Correcting the optimally selected resampling-based error rate: A smooth analytical alternative to nested cross-validation

Anne-Laure Boulesteix, Thomas Augustin, Christoph Bernau, 2011 .

Over-optimism in bioinformatics: an illustration

Anne-Laure Boulesteix, Arthur Tenenhaus, Korbinian Strimmer, 2010, Bioinform..

Bmc Medical Research Methodology Open Access Optimal Classifier Selection and Negative Bias in Error Rate Estimation: an Empirical Study on High-dimensional Prediction

Anne-Laure Boulesteix, Carolin Strobl, A. Boulesteix, 2022 .

A Framework to Discover Emerging Patterns for Application in Microarray Data

Gerhard Tutz, Anne-Laure Boulesteix, A. Boulesteix, 2003 .

Identification of interaction patterns and classification with applications to microarray data

Gerhard Tutz, Anne-Laure Boulesteix, A. Boulesteix, 2006, Comput. Stat. Data Anal..

Making complex prediction rules applicable for readers: Current practice in random forest literature and recommendations

Philipp Probst, Roman Hornung, Anne-Laure Boulesteix, 2018, Biometrical journal. Biometrische Zeitschrift.

IPF-LASSO: Integrative L 1-Penalized Regression with Penalty Factors for Prediction Based on Multi-Omics Data

Xiaoyu Jiang, Anne-Laure Boulesteix, Mathias Fuchs, 2017, Comput. Math. Methods Medicine.

Investigating the prediction ability of survival models based on both clinical and omics data: two case studies

Anne-Laure Boulesteix, Willi Sauerbrei, Riccardo De Bin, 2014, Statistics in medicine.

Added predictive value of omics data: specific issues related to validation illustrated by two case studies

Anne-Laure Boulesteix, Riccardo De Bin, Tobias Herold, 2014, BMC Medical Research Methodology.

Correcting the Optimal Resampling‐Based Error Rate by Estimating the Error Rate of Wrapper Algorithms

Anne-Laure Boulesteix, Thomas Augustin, Christoph Bernau, 2013, Biometrics.

A Plea for Neutral Comparison Studies in Computational Sciences

Anne-Laure Boulesteix, Manuel J. A. Eugster, A. Boulesteix, 2012, PloS one.

Stochastic modeling for the COMET-assay

Anne-Laure Boulesteix, Volkmar Liebscher, Volker Hösel, 2003 .

Microarray-based classification and clinical predictors: on combined classifiers and additional predictive value

Anne-Laure Boulesteix, Martin Daumer, Christine Porzelius, 2008, Bioinform..

Subsampling versus bootstrapping in resampling‐based model selection for multivariable regression

Anne-Laure Boulesteix, Willi Sauerbrei, Silke Janitza, 2016, Biometrics.

Assessment of predictive performance in incomplete data by combining internal validation and multiple imputation

Anne-Laure Boulesteix, Simone Wahl, Astrid Zierer, 2016, BMC Medical Research Methodology.

Hyperparameter optimization: Foundations, algorithms, best practices, and open challenges

A. Boulesteix, M. Lindauer, B. Bischl, 2021, WIREs Data. Mining. Knowl. Discov..

A replication crisis in methodological research?

Anne-Laure Boulesteix, Sabine Hoffmann, Heidi Seibold, 2020, Significance.

Publication Bias in Methodological Computational Research

Anne-Laure Boulesteix, Alexander Hapfelmeier, Veronika Stierle, 2015, Cancer informatics.

An AUC-based permutation variable importance measure for random forests

A. Boulesteix, C. Strobl, Silke Janitza, 2013, BMC Bioinformatics.

Random forest versus logistic regression: a large-scale benchmark experiment

A. Boulesteix, Philipp Probst, R. Couronné, 2018, BMC Bioinform..

Interleukin-22 is elevated in lavage from patients with lung cancer and other pulmonary diseases

A. Boulesteix, M. Edelmann, F. Gamarra, 2016, BMC Cancer.

Combining location-and-scale batch effect adjustment with data cleaning by latent factor adjustment

David Causeur, Roman Hornung, Anne-Laure Boulesteix, 2016, BMC Bioinformatics.

On the Simultaneous Analysis of Clinical and Omics Data: A Comparison of Globalboosttest and Pre-validation Techniques

Anne-Laure Boulesteix, Margret-Ruth Oelker, A. Boulesteix, 2013, Statistical Models for Data Analysis.

Testing the additional predictive value of high-dimensional molecular data

Torsten Hothorn, Anne-Laure Boulesteix, A. Boulesteix, 2010, BMC Bioinformatics.

Comments on: Augmenting the bootstrap to analyze high dimensional genomic data

Anne-Laure Boulesteix, Athanassios Kondylis, Nicole Krämer, 2008 .

Outcome of patients treated with extracorporeal life support in cardiogenic shock complicating acute myocardial infarction: 1-year result from the ECLS-Shock study

A. Boulesteix, J. Hausleiter, A. Bauer, 2020, Clinical Research in Cardiology.

Benchmarking for Clustering Methods Based on Real Data: A Statistical View

Anne-Laure Boulesteix, Myriam Hatz, A. Boulesteix, 2017 .

Use of Resampling Procedures to Investigate Issues of Model Building and Its Stability

Anne-Laure Boulesteix, Willi Sauerbrei, A. Boulesteix, 2019 .

Validation of cluster analysis results on validation data: A systematic framework

A. Boulesteix, C. Hennig, Theresa Ullmann, 2021, WIREs Data Mining Knowl. Discov..

Regularized estimation of large-scale gene association networks using graphical Gaussian models

Anne-Laure Boulesteix, Juliane Schäfer, Nicole Krämer, 2009, BMC Bioinformatics.

Comparing the vibration of effects due to model, data pre-processing and sampling uncertainty on a large data set in personality psychology

Anne-Laure Boulesteix, John Ioannidis, Felix D. Schönbrodt, 2020, Meta-Psychology.

WilcoxCV: an R package for fast variable selection in cross-validation

Anne-Laure Boulesteix, A. Boulesteix, 2007, Bioinform..

Examining the robustness of observational associations to model, measurement and sampling uncertainty with the vibration of effects framework

Anne-Laure Boulesteix, Sabine Hoffmann, John Ioannidis, 2020, International journal of epidemiology.

Single-center versus multi-center data sets for molecular prognostic modeling: a simulation study

A. Boulesteix, C. Belka, R. Hornung, 2020, Radiation oncology.

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.

Modelling Individual Response to Treatment and Its Uncertainty:A Review of Statistical Methods and Challenges for Future Research

Anne-Laure Boulesteix, Ulrich Mansmann, A. Boulesteix, 2020 .

Relationship between age at initiation of cysteamine treatment, adherence with therapy, and glomerular kidney function in infantile nephropathic cystinosis.

A. Boulesteix, W. Gahl, B. Tönshoff, 2022, Molecular genetics and metabolism.

Stereotactic Radiosurgery versus Whole-Brain Radiotherapy in Patients with 4-10 Brain Metastases: A Nonrandomized Controlled Trial.

A. Boulesteix, U. Mansmann, C. Belka, 2023, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

Maximally selected Chi-squared statistics and non-monotonic associations: An exact approach based on two cutpoints

Carolin Strobl, Anne-Laure Boulesteix, A. Boulesteix, 2007, Comput. Stat. Data Anal..

Improved prediction of complex diseases by common genetic markers: state of the art and further perspectives

A. Boulesteix, H. Kirsten, J. Brauer, 2016, Human Genetics.

The Normal Fetal Heart Rate Study: Analysis Plan

Anne-Laure Boulesteix, Martin Daumer, Wolfgang Hatzmann, 2007 .

Regularized estimation of large-scale gene association networks using graphical Gaussian models

A. Boulesteix, J. Schäfer, Nicole Krämer, 2009, BMC Bioinformatics.

Optimal classifier selection and negative bias in error rate estimation: an empirical study on high-dimensional prediction

A. Boulesteix, C. Strobl, Carolin Strobl, 2009, BMC medical research methodology.

On representative and illustrative comparisons with real data in bioinformatics: response to the letter to the editor by Smith et al

Anne-Laure Boulesteix, A. Boulesteix, 2013, Bioinform..

Explaining the optimistic performance evaluation of newly proposed methods: A cross‐design validation experiment

Department of Statistics, A. Boulesteix, Sabine Hoffmann, 2022, Biometrical journal. Biometrische Zeitschrift.

Reader's Reaction to "Dimension Reduction for Classification with Gene Expression Microarray Data" by Dai et al (2006)

Anne-Laure Boulesteix, A. Boulesteix, 2006, Statistical applications in genetics and molecular biology.

Interaction forests: Identifying and exploiting interpretable quantitative and qualitative interaction effects

Roman Hornung, Anne-Laure Boulesteix, A. Boulesteix, 2021, Comput. Stat. Data Anal..

Partial least squares: a versatile tool for the analysis of high-dimensional genomic data

A. Boulesteix, K. Strimmer, 2007, Briefings Bioinform..

A white paper on good research practices in benchmarking: The case of cluster analysis

A. Boulesteix, F. Leisch, D. Steinley, 2023, WIREs Data Mining and Knowledge Discovery.

From RNA sequencing measurements to the final results: A practical guide to navigating the choices and uncertainties of gene set analysis

A. Boulesteix, L. C. Hinske, P. Callahan, 2023, WIREs Computational Statistics.

Predicting transcription factor activities from combined analysis of microarray and ChIP data: a partial least squares approach

A. Boulesteix, K. Strimmer, F. Boas, 2005, Theoretical Biology and Medical Modelling.

Boulesteix, Strimmer: Partial Least Squares: a Versatile Tool for the Analysis of High-dimensional Genomic Data Projektpartner Partial Least Squares: a Versatile Tool for the Analysis of High-dimensional Genomic Data

A. Boulesteix, K. Strimmer, 2022 .

Over-optimism in bioinformatics: an illustration

A. Boulesteix, K. Strimmer, A. Tenenhaus, 2010, Bioinform..

Effective methods to enhance medical students’ cardioversion and transcutaneous cardiac pacing skills retention - a prospective controlled study

A. Boulesteix, S. Harendza, Christian Kowalski, 2022, BMC medical education.

Boulesteix , Strimmer : Partial Least Squares : A Versatile Tool for the Analysis of High-Dimensional Genomic Data

A. Boulesteix, K. Strimmer, 2007 .

Hyperparameter optimization: Foundations, algorithms, best practices, and open challenges pdf

Bernd Bischl, Anne-Laure Boulesteix, Marius Lindauer, 2021, WIREs Data. Mining. Knowl. Discov..

Improving Cross-study Prediction through Addon Batch Effect Adjustment and Addon Normalization Improving Cross-study Prediction through Addon Batch Effect Adjustment and Addon Normalization

A. Boulesteix, R. Hornung, C. Bernau, 2022 .

Stability and aggregation of ranked gene lists

A. Boulesteix, M. Slawski, 2009, Briefings Bioinform..

Full versus incomplete cross-validation: measuring the impact of imperfect separation between training and test sets in prediction error estimation

Roman Hornung, Caroline Truntzer, Anne-Laure Boulesteix, 2014 .

PLS dimension reduction for classification of microarray data

A. Boulesteix, 2004 .

TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods

A. Boulesteix, S. Denaxas, M. van Smeden, 2024, BMJ.

Theoretical Biology and Medical Modelling Open Access Predicting Transcription Factor Activities from Combined Analysis of Microarray and Chip Data: a Partial Least Squares Approach

A. Boulesteix, K. Strimmer, 2022 .

TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods

A. Boulesteix, G. Varoquaux, M. Sendak, 2024, BMJ.

Over-optimistic evaluation and reporting of novel cluster algorithms: an illustrative study

A. Boulesteix, Theresa Ullmann, T. Seidl, 2022, Advances in Data Analysis and Classification.

Molecular Differences between Chronic and Aggressive Periodontitis

A. Boulesteix, P. Papapanou, P. Guarnieri, 2013, Journal of dental research.

Bias in random forest variable importance measures: Illustrations, sources and a solution

A. Boulesteix, T. Hothorn, A. Zeileis, 2007, BMC Bioinformatics.

To tweak or not to tweak. How exploiting flexibilities in gene set analysis leads to over-optimism

A. Boulesteix, Milena Wunsch, L. Hinske, 2024, 2402.00754.

Raising awareness of uncertain choices in empirical data analysis: A teaching concept toward replicable research practices

A. Boulesteix, Sabine Hoffmann, Maximilian M Mandl, 2024, PLoS computational biology.

Addressing researcher degrees of freedom through minP adjustment

A. Boulesteix, Sabine Hoffmann, L. Hinske, 2024, BMC medical research methodology.

Over-optimism in bioinformatics research

A. Boulesteix, 2010, Bioinform..

Validation in bioinformatics and molecular medicine. Editorial.

Anne-Laure Boulesteix, A. Boulesteix, 2011, Briefings in bioinformatics.

A comparison of hyperparameter tuning procedures for clinical prediction models: A simulation study

A. Boulesteix, M. van Smeden, B. Van Calster, 2024, Statistics in medicine.

Boulesteix : Maximally selected chi-square statistics and binary splits of nominal variables

A. Boulesteix, 2007 .

Random Forests for Ordinal Response Data: Prediction and Variable Selection

Gerhard Tutz, Anne-Laure Boulesteix, Silke Janitza, 2014 .