RnBeads 2.0: comprehensive analysis of DNA methylation data F Müller, M Scherer, Y Assenov, P Lutsik, J Walter, T Lengauer, C Bock Genome biology 20, 1-12, 2019 | 236 | 2019 |
Quantitative comparison of within-sample heterogeneity scores for DNA methylation data M Scherer, A Nebel, A Franke, J Walter, T Lengauer, C Bock, F Müller, ... Nucleic acids research 48 (8), e46-e46, 2020 | 43 | 2020 |
Guidelines for cell-type heterogeneity quantification based on a comparative analysis of reference-free DNA methylation deconvolution software C Decamps, F Privé, R Bacher, D Jost, A Waguet, EA Houseman, E Lurie, ... BMC bioinformatics 21, 1-15, 2020 | 38 | 2020 |
DNA methylation-based prediction of response to immune checkpoint inhibition in metastatic melanoma K Filipski, M Scherer, KN Zeiner, A Bucher, J Kleemann, P Jurmeister, ... Journal for immunotherapy of cancer 9 (7), 2021 | 30 | 2021 |
Clonally resolved single-cell multi-omics identifies routes of cellular differentiation in acute myeloid leukemia S Beneyto-Calabuig, AK Merbach, JA Kniffka, M Antes, C Szu-Tu, ... Cell Stem Cell 30 (5), 706-721. e8, 2023 | 25 | 2023 |
Reference-free deconvolution, visualization and interpretation of complex DNA methylation data using DecompPipeline, MeDeCom and FactorViz M Scherer, PV Nazarov, R Toth, S Sahay, T Kaoma, V Maurer, ... Nature Protocols 15 (10), 3240-3263, 2020 | 23 | 2020 |
Longitudinal multi-omics analysis identifies early blood-based predictors of anti-TNF therapy response in inflammatory bowel disease N Mishra, K Aden, JI Blase, N Baran, D Bordoni, F Tran, C Conrad, ... Genome medicine 14 (1), 110, 2022 | 21 | 2022 |
Machine learning for deciphering cell heterogeneity and gene regulation M Scherer, F Schmidt, O Lazareva, J Walter, J Baumbach, MH Schulz, ... Nature Computational Science 1 (3), 183-191, 2021 | 17 | 2021 |
scTAM-seq enables targeted high-confidence analysis of DNA methylation in single cells A Bianchi, M Scherer, R Zaurin, K Quililan, L Velten, R Beekman Genome Biology 23 (229), 2022 | 16 | 2022 |
Weighted elastic net for unsupervised domain adaptation with application to age prediction from DNA methylation data L Handl, A Jalali, M Scherer, R Eggeling, N Pfeifer Bioinformatics 35 (14), i154-i163, 2019 | 15 | 2019 |
Prenatal exposure to endocrine disrupting chemicals is associated with altered DNA methylation in cord blood K Mattonet, N Nowack-Weyers, V Vogel, D Moser, S Tierling, ... Epigenetics 17 (9), 935-952, 2022 | 8 | 2022 |
Bisulfite profiling of the MGMT promoter and comparison with routine testing in glioblastoma diagnostics S Tierling, WM Jürgens-Wemheuer, A Leismann, J Becker-Kettern, ... Clinical Epigenetics 14 (1), 26, 2022 | 4 | 2022 |
Identification of tissue-specific and common methylation quantitative trait loci in healthy individuals using MAGAR M Scherer, G Gasparoni, S Rahmouni, T Shashkova, M Arnoux, E Louis, ... Epigenetics & Chromatin, 2021 | 3 | 2021 |
Dissecting DNA Methylation in Human Aging M Scherer Universität des Saarlandes Saarbrücken, 2016 | 2 | 2016 |
Somatic epimutations enable single-cell lineage tracing in native hematopoiesis across the murine and human lifespan M Scherer, I Singh, M Braun, C Szu-Tu, M Kardorff, J Rühle, R Frömel, ... bioRxiv, 2024 | | 2024 |
EpiCHAOS: a metric to quantify epigenomic heterogeneity in single-cell data K Kelly, M Scherer, MM Braun, P Lutsik, C Plass bioRxiv, 2024.04. 24.590899, 2024 | | 2024 |
Alterations in the hepatocyte epigenetic landscape in steatosis RK Maji, B Czepukojc, M Scherer, S Tierling, C Cadenas, K Gianmoena, ... Epigenetics & Chromatin 16 (1), 30, 2023 | | 2023 |
Computational solutions for addressing heterogeneity in DNA methylation data M Scherer Saarländische Universitäts-und Landesbibliothek, 2020 | | 2020 |