Carl Herrmann
Carl Herrmann
Lecturer - Health Data Science Unit - BioQuant and Medical Faculty Heidelberg
Verified email at - Homepage
Cited by
Cited by
Pan-cancer analysis of whole genomes
Nature 578 (7793), 82-93, 2020
Telomerase activation by genomic rearrangements in high-risk neuroblastoma
M Peifer, F Hertwig, F Roels, D Dreidax, M Gartlgruber, R Menon, ...
Nature 526 (7575), 700-704, 2015
Identification of regulatory networks in HSCs and their immediate progeny via integrated proteome, transcriptome, and DNA methylome analysis
N Cabezas-Wallscheid, D Klimmeck, J Hansson, DB Lipka, A Reyes, ...
Cell stem cell 15 (4), 507-522, 2014
Atypical teratoid/rhabdoid tumors are comprised of three epigenetic subgroups with distinct enhancer landscapes
PD Johann, S Erkek, M Zapatka, K Kerl, I Buchhalter, V Hovestadt, ...
Cancer cell 29 (3), 379-393, 2016
Analyses of non-coding somatic drivers in 2,658 cancer whole genomes
E Rheinbay, MM Nielsen, F Abascal, JA Wala, O Shapira, G Tiao, ...
Nature 578 (7793), 102-111, 2020
Myelodysplastic cells in patients reprogram mesenchymal stromal cells to establish a transplantable stem cell niche disease unit
H Medyouf, M Mossner, JC Jann, F Nolte, S Raffel, C Herrmann, A Lier, ...
Cell stem cell 14 (6), 824-837, 2014
Decoding the regulatory landscape of melanoma reveals TEADS as regulators of the invasive cell state
A Verfaillie, H Imrichova, ZK Atak, M Dewaele, F Rambow, G Hulselmans, ...
Nature communications 6 (1), 1-16, 2015
RSAT 2011: regulatory sequence analysis tools
M Thomas-Chollier, M Defrance, A Medina-Rivera, O Sand, C Herrmann, ...
Nucleic acids research 39 (suppl_2), W86-W91, 2011
RSAT 2015: regulatory sequence analysis tools
A Medina-Rivera, M Defrance, O Sand, C Herrmann, ...
Nucleic acids research 43 (W1), W50-W56, 2015
RSAT peak-motifs: motif analysis in full-size ChIP-seq datasets
M Thomas-Chollier, C Herrmann, M Defrance, O Sand, D Thieffry, ...
Nucleic acids research 40 (4), e31-e31, 2012
BCAT1 restricts αKG levels in AML stem cells leading to IDHmut-like DNA hypermethylation
S Raffel, M Falcone, N Kneisel, J Hansson, W Wang, C Lutz, L Bullinger, ...
Nature 551 (7680), 384-388, 2017
Genome-wide DNA-methylation landscape defines specialization of regulatory T cells in tissues
M Delacher, CD Imbusch, D Weichenhan, A Breiling, A Hotz-Wagenblatt, ...
Nature immunology 18 (10), 1160-1172, 2017
i-cisTarget: an integrative genomics method for the prediction of regulatory features and cis-regulatory modules
C Herrmann, B Van de Sande, D Potier, S Aerts
Nucleic acids research 40 (15), e114-e114, 2012
Clustering proteins from interaction networks for the prediction of cellular functions
C Brun, C Herrmann, A Guénoche
BMC bioinformatics 5 (1), 1-11, 2004
Deconvolution of single-cell multi-omics layers reveals regulatory heterogeneity
L Liu, C Liu, A Quintero, L Wu, Y Yuan, M Wang, M Cheng, L Leng, L Xu, ...
Nature communications 10 (1), 1-10, 2019
A complete workflow for the analysis of full-size ChIP-seq (and similar) data sets using peak-motifs
M Thomas-Chollier, E Darbo, C Herrmann, M Defrance, D Thieffry, ...
Nature protocols 7 (8), 1551-1568, 2012
A comprehensive comparison of tools for differential ChIP-seq analysis
S Steinhauser, N Kurzawa, R Eils, C Herrmann
Briefings in bioinformatics 17 (6), 953-966, 2016
Compactification of type IIB string theory on Calabi–Yau threefolds
R Böhm, H Günther, C Herrmann, J Louis
Nuclear Physics B 569 (1-3), 229-246, 2000
Connectivity distribution of spatial networks
C Herrmann, M Barthélemy, P Provero
Physical Review E 68 (2), 026128, 2003
Environment‐induced epigenetic reprogramming in genomic regulatory elements in smoking mothers and their children
T Bauer, S Trump, N Ishaque, L Thürmann, L Gu, M Bauer, M Bieg, Z Gu, ...
Molecular Systems Biology 12 (3), 861, 2016
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