Publications

• S. Nowakowski, P. Pokarowski, W. Rejchel, A. Soltys, Improving Group Lasso for high-dimensional categorical data International Conference on Computational Science (ICCS) 2023. Supplemental Material


• P. Pokarowski, W. Rejchel, A. Soltys, M. Frej and J. Mielniczuk, Improving Lasso for model selection and prediction Scandinavian Journal of Statistics, https://doi.org/10.1111/sjos.12546, 2021.


• M. Metrak, P. Pokarowski, M. Sulwinski, A. Gantumur and M. Suska-Malawska, Plant response to N availability in permafrost-affected alpine wetlands in arid and semi-arid climate zones Science of the Total Environment, 721, 137791, 2020.


• T. Bem, P. Pokarowski and P. Meyrand, Do Altruists Like Equity? Social Psychological Bulletin, e28284, 14(1), 2019.


• A. Maj-Kanska, P. Pokarowski and A. Prochenka, Delete or merge regressors for linear model selection. Electronic Journal of Statistics, 9, 1749-1778, 2015. Package DMR on CRAN


• P. Pokarowski and J. Mielniczuk, Combined l1 and greedy l0 penalized least squares for linear model selection. Journal of Machine Learning Research, 16, 961-992, 2015. Supplemental Material


• A. Prochenka, P. Pokarowski, P. Gasperowicz, J. Kosinska, P.Stawinski, R. Zbiec-Piekarska, M. Spolnicka, W. Branicki and R. Ploski, A cautionary note on using binary calls for analysis of DNA methylation . Bioinformatics, 31(9), 1519-1520, 2015.


• L. Gajek, W. Niemiro and P. Pokarowski, Optimal Monte Carlo integration with fixed relative precision. Journal of Complexity, 29, 4-26, 2013.


• D. Rabczenko, P. Pokarowski, B. Wojtyniak and A. Poznanska, Mortality atlas as a useful tool for detecting unexpected spatial patterns of mortality in Poland. European Journal of Public Health, 22, Supplement: 2, 157-158, 2012. Web version of the mortality atlas (in Polish)


• J. Mieczkowski, M. E. Tyburczy, M. Dabrowski and P. Pokarowski, Probe set filtering increases correlation between Affymetrix GeneChip and qRT-PCR expression measurements. BMC Bioinformatics, 11:104, 2010.


• M. E. Tyburczy, K. Kotulska, P. Pokarowski, J. Mieczkowski, J. Kucharska, W. Grajkowska, M. Roszkowski, S. Jozwiak and B. Kaminska, Novel proteins regulated by mTOR in subependymal giant cell astrocytomas of patients with tuberous sclerosis complex and new therapeutic implications . American Journal of Pathology, 176, 1878-1890, 2010.


• W. Niemiro and P. Pokarowski, Fixed Precision MCMC estimation by Median of Products of Averages. Journal of Applied Probability, 46(2), 309-329, 2009.


• A. Kloczkowski, R. L. Jernigan, Z. Wu, G. Song, L. Yang, A. Kolinski, P. Pokarowski, Distance matrix-based approach to protein structure prediction. Journal of Structural and Functional Genomics, 10(1), 67-81, 2009.


• A. Gambin, P. Krzyzanowski and P. Pokarowski, Aggregation Algorithms for Perturbed Markov Chains with Applications to Networks Modeling. SIAM Journal on Scientific Computing, 31(1), 45-73, 2008.


• S. Kawashima, P. Pokarowski, M. Pokarowska, A. Kolinski, T. Katayama and M. Kanehisa, AAindex: amino acid index database, progress report 2008. Nucleic Acids Research 36 (Suppl.1), D202-D205, 2008. AAindex database


• P. Pokarowski, A. Kloczkowski, S. Nowakowski, M. Pokarowska, R. L. Jernigan and A. Kolinski, Ideal amino acid exchange forms for approximating substitution matrices. Proteins: Structure, Function and Bioinformatics, 69, 379-393, 2007. Supplemental Material


• P. Pokarowski, K. Droste and A. Kolinski, A minimal protein-like lattice model: an alpha-helix motif. Journal of Chemical Physics, 122, art. no. 214915, 1-6, 2005.


• P. Pokarowski, A. Kloczkowski, R. L. Jernigan, N. Kothari, M. Pokarowska and A. Kolinski, Inferring ideal amino acid interaction forms from statistical protein contact potentials. Proteins: Structure, Function and Bioinformatics, 59(1), 49-57, 2005. Supplemental Material


• A. Kolinski, D. Gront, P. Pokarowski and J. Skolnick, A simple lattice model that exhibits a protein-like cooperative all-or-none folding transition. Biopolymers, 69(3), 399-405, 2003.


• P. Pokarowski, A. Kolinski and J. Skolnick, A minimal physically realistic protein-like lattice model: Designing an energy landscape that ensures all-or-none folding to a unique native state. Biophysical Journal, 84(3), 1518-1526, 2003.


• A. Gambin and P. Pokarowski, A new combinatorial algorithm for large Markov chains. Computer Algebra in Scientific Computing - CASC 2001, V.G. Ghanza, E.W. Mayr, E.V. Vorozthsov (Eds.), Springer, Berlin 2001, pp. 195-212.


• A. Gambin and P. Pokarowski, A combinatorial aggregation algorithm for computing stationary distributions of large Markov chains. Fundamentals of Computation Theory 13th International Symposium - FCT 2001, R. Freivalds (Ed.), Springer LNCS 2138, 2001, pp. 384-388.


• J. Jachymski, L. Gajek and P. Pokarowski, The Tarski-Kantorovitch principle and the theory of iterated function systems. Bulletin of the Australian Mathematical Society, 61, 247-261, 2000.


• A. Kierzek, P. Pokarowski and P. Zielenkiewicz, Microscopic model of protein crystal growth. Biophysical Chemistry, 87(1), 43-61, 2000.


• A. Kierzek, P. Pokarowski and P. Zielenkiewicz, Lattice simulation of protein crystal formation. Biophysical Chemistry, 77, 123-137, 1999.


• P. Pokarowski, Directed forests with applications to algorithms related to Markov chains. Applicationes Mathematicae, 26(4), 395-414, 1999.


• P. Pokarowski, Directed forests and algorithms related to Markov chains (in Polish). PhD thesis, Institute of Mathematics of the Polish Academy of Sciences, 1998.


• P. Pokarowski, Uncoupling measures and eigenvalues of stochastic matrices. Journal of Applied Analysis, 4(2), 261-269, 1998.


• W. Niemiro and P. Pokarowski, Tail events of some nonhomogeneous Markov chains. Annals of Applied Probability, 5(1), 261-293, 1995.