Monography

• Phenotypes and Genotypes: The Search for Influential Genes (with F. Frommlet and D. Ramsey), Springer Series in Computational Biology, 2016.

Preprints and new publications (from 2010)

• Pattern recovery by SLOPE (with X. Dupuis, P. Graczyk, B. Kolodziejek, T. Skalski, P. Tardivel and M. Wilczynsk), 2022.

• Sparse Graphical Modelling via the Sorted L-Norm (with R. Riccobello, G. Bonaccolto, P.J. Kremer, S. Paterlini and P. Sobczyk), 2022.

• Sparse Graphical Modelling for Minimum Variance Portfolios (with R. Riccobello, G. Bonaccolto, P.J. Kremer and S. Paterlini), 2022.

• Selecting predictive biomarkers from genomic data (with F. Frommlet, P. Szulc and F. Koenig), PloS One, 2022.

• Predicting the redshift of gamma-ray loud AGNs using Supervised Machine Learning: Part 2 (with A. Narendra, S. J. Gibson, M. G. Dainotti, A. Pollo, I. Liodakis, A. Poliszczuk), The Astrophysical Journal Supplement Series, 2022.

• A power analysis for knockoffs with the lasso coefficient-difference statistic (with A. Weinstein, W.J. Su, R.F. Barber, E.J. Candes), 2020.

• VARCLUST: clustering variables using dimensionality reduction (with P. Sobczyk, S. Wilczynski, P. Graczyk, J. Josse, F. Panloup, V. Seegers, M. Staniak), 2020.

• Identifying important predictors in large data bases - multiple testing and model selection (with F. Frommlet), Handbook of Multiple Comparisons, 2022.

• Adaptive bayesian SLOPE - high-dimensional model selection with missing values (with W. Jiang, J. Josse, B. Miasojedow, V. Rockova, TB Group), Journal of Computational and Graphical Statistics, 2022.

• Predicting the redshift of gamma-ray loud AGNs using supervised machine learning (with M. G. Dainotti, A. Narendra, S. J. Gibson, B. Miasojedow, I. Liodakis, A. Pollo, T. Nelson, K. Wozniak, Z. Nguyen, J. Larrson), Astrophysical Journal, 2021.

• Ghost QTL and hotspots in experimental crosses: novel approach for modeling polygenic effects (with J. Wallin, P.A. Szulc, R.W. Doerge, D.O. Siegmund), Genetics, 2021.

• The strong screening rule for SLOPE (with J. Larsson, J. Wallin), NeurIPS, 2020.

• Sparse Index Clones via the Sorted L1-Norm (with P. Kremmer, D. Brzyski and S. Paterlini), Quantitative Finance, DOI: 10.1080/14697688.2021.1962539, 2021.

• Rank-based Lasso--efficient methods for high-dimensional robust model selection (with W. Rejchel), Journal of Machine Learning Research, 2020.

• On the asymptotic properties of slope (with M. Kos), Sankhya A, 2020.

• Classification of human physical activity based on raw accelerometry data via spherical coordinate transformation (with M. Kos, N. Glynn, J.Harezlak), Statistics in Medicine, 2020.

• Discussion of ''A Novel Algorithmic Approach to Bayesian Logic Regression'' by A. Hubin, G. Storvik, F. Frommlet (with B. Miasojedow, J. Wallin), Bayesian Analysis, 2020.

• Structure Learning of Gaussian Markov Random Fields with False Discovery Rate Control (with S. Lee, P. Sobczyk), Symmetry 2019.

• On the sign recovery by LASSO, thresholded LASSO and thresholded Basis Pursuit Denoising (with P.J.C. Tardivel), Scandinavian Journal of Statistics, 2022.

• Lessons learned from IDeAl-33 recommendations from the IDeAl-net about design and analysis of small population clinical trials(with R.-D.Hilgers, C.F.Burman, H.Dette, M.Karlsson, F.Koenig, C.Male, F.Mentre, G.Molenberghs and S.Senn), Orphanet Journal of Rare Diseases, 2018.

• High-dimensional robust regression and outliers detection with SLOPE (with A. Virouleau, A. Guilloux and S. Gaiffas).

• Integrated Design and Analysis of small population group trials, IDEAL, FP7 (with R-D.Hilgers, C.F.Burman, H.Dette, M.Karlsson, F.Koenig, C.Male, F.Mentre, G.Molenberghs, S.Senn), Impact, Volume 2017, Number 4, May 2017, pp. 14-16(3), 2017.

• Sparse Portfolio Selection via the sorted l1-Norm (with P. J. Kremer, S. Lee and S. Paterlini), Journal of Banking & Finance 110, 2020.

• Controlling the rate of GWAS false discoveries (with D.Brzyski, C.B. Peterson, P. Sobczyk, E.J. Candes and C. Sabatti), Genetics 205(1): 61-75, 2017.
• geneSLOPE R package, maintainer: P. Sobczyk

• Joint Genotype- and Ancestry-based Genome-wide Association Studies in Admixed Populations (with P.Szulc, F. Frommlet and H. Tang), Genetic Epidemiology 41(6):555-566, 2017.
• admixtures R package, maintainer: P. Szulc

• Bayesian dimensionality reduction with PCA using penalized semi-integrated likelihood (with P. Sobczyk and J. Josse), Journal of Computational and Graphical Statistics, 26, 826--839, 2017.
• PESEL R package, maintainer: P. Sobczyk

• Group SLOPE - adaptive selection of groups of predictors, with D. Brzyski, A. Gossmann and W. Su), Journal of the American Statistical Association, 114:525, 419-433, 2019.
• grpSLOPE R package, maintainer: A. Gossmann

• Fast Saddle-Point Algorithm for Generalized Dantzig Selector and FDR Control with the Ordered $\ell_1$-Norm (with S. Lee and D. Brzyski), Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, JMLR:W&CP, vol.51, 780--789, 2016.

• False Discoveries Occur Early on the Lasso Path (with W. Su and E. J. Candes), Annals of Statistics, 45 (5), 2133 -- 2150, 2017.

• SLOPE -- Adaptive Variable Selection via Convex Optimization (with E. van den Berg, C. Sabatti, W. Su and E. J. Candes), Annals of Applied Statistics 2015, Vol. 9, No. 3, 1103-1140.
• SLOPE R package, maintainer: E. Patterson

• Detection of epistatic effects with logic regression and a classical linear regression model (with M. Malina, K. Ickstadt, H. Schwender, M. Posch),SAGMB, 2014.

• Statistical Estimation and Testing via the Sorted l1 Norm (with E. van den Berg, W. Su and E. J. Candes), Preprint, 2013.

• Some optimality properties of FDR controlling rules under sparsity (with F. Frommlet), Electronic Journal of Statistics, 2013.

• Localizing Influential Genes with Modified Versions of Bayesian Information Criterion (with P. Szulc), Mathematica Applicanda, 2012.

• QTL Mapping Using a Memetic Algorithm with Modifications of BIC as Fitness Function. (with F. Frommlet, H. Arnardottir and I. Ljubic), SAGMB, 2012

• Model Selection and Multiple Testing - A Bayesian and Empirical Bayes Overview and some New Results (with R. Dutta and J.K. Ghosh),Golden Volume of Journal of the Indian Statistical Association, 2012

• Modified versions of Bayesian Information Criterion for genome-wide association studies (with F. Frommlet, F. Ruhaltinger and P. Twarog), CSDA, 2012

• Asymptotic Bayes optimality under sparsity for generally distributed effect sizes under the alternative. (with F.Frommlet, A. Chakrabarti and M. Murawska), Preprint, 2012

• Asymptotic Bayes-optimality under sparsity of some multiple testing procedures (with A. Chakrabarti, F. Frommlet and J.K. Ghosh) Annals of Statistics, 2011

• The Bayes oracle and asymptotic optimality of multiple testing procedures under sparsity (with A. Chakrabarti, F. Frommlet and J.K. Ghosh), early extended version of the paper from Annals of Statistics

• Modified versions of Bayesian Information Criterion for sparse Generalized Linear Models (with M. Zak-Szatkowska), CSDA, 2011

• Locating multiple interacting quantitative trait loci with the zero-inflated generalized Poisson regression, (with V. Erhardt and C. Czado), SAGMB, 2010

• Data driven smooth tests for bivariate normality, Extended version of the paper from Journal of Multivariate Normality, 1999