BiQ Analyzer HT: locus-specific analysis of DNA methylation by high-throughput bisulfite sequencing. - Pavlo Lutsik; Lars Feuerbach; Julia Arand; Thomas Lengauer; Jörn Walter; Christoph Bock (Nucleic Acids Res., 2011)

Matrix factorization with binary components. - Martin Slawski; Matthias Hein 001; Pavlo Lutsik (NIPS, 2013)

AKSmooth: Enhancing low-coverage bisulfite sequencing data via kernel-based smoothing. - Junfang Chen; Pavlo Lutsik; Ruslan Akulenko; Jörn Walter; Volkhard Helms (J. Bioinform. Comput. Biol., 2014)

BiQ Analyzer HiMod: an interactive software tool for high-throughput locus-specific analysis of 5-methylcytosine and its oxidized derivatives. - Daniel Becker 006; Pavlo Lutsik; Peter Ebert; Christoph Bock; Thomas Lengauer; Jörn Walter (Nucleic Acids Res., 2014)

Identification and analysis of methylation call differences between bisulfite microarray and bisulfite sequencing data with statistical learning techniques. - Matthias Döring; Gilles Gasparoni; Jasmin Gries; Karl Nordström; Pavlo Lutsik; Jörn Walter; Nico Pfeifer (BMC Bioinform., 2015)

Guidelines for cell-type heterogeneity quantification based on a comparative analysis of reference-free DNA methylation deconvolution software. - Clémentine Decamps; Florian Privé; Raphael Bacher; Daniel Jost 002; Arthur Waguet; Eugene Andres Houseman; Eugene Lurie; Pavlo Lutsik; Aleksandar Milosavljevic; Michael Scherer; Michael G. B. Blum; Magali Richard (BMC Bioinform., 2020)

Methrix: an R/Bioconductor package for systematic aggregation and analysis of bisulfite sequencing data. - Anand Mayakonda; Maximilian Schönung; Joschka Hey; Rajbir Nath Batra; Clarissa Feuerstein-Akgoz; Kristin Köhler; Daniel B. Lipka; Rocio Sotillo; Christoph Plass; Pavlo Lutsik; Reka Toth (Bioinform., 2021)

Systematic evaluation of cell-type deconvolution pipelines for sequencing-based bulk DNA methylomes. - Yunhee Jeong; Lisa Barros de Andrade e Sousa; Dominik Thalmeier; Reka Toth; Marlene Ganslmeier; Kersten Breuer; Christoph Plass; Pavlo Lutsik (Briefings Bioinform., 2022)

scMaui: a widely applicable deep learning framework for single-cell multiomics integration in the presence of batch effects and missing data. - Yunhee Jeong; Jonathan Ronen; Wolfgang Kopp; Pavlo Lutsik; Altuna Akalin (BMC Bioinform., 2024)