The Biomedical Genomics group at the Health Data Science Unit, Medical Faculty Heidelberg and BioQuant is focusing on deciphering the molecular mechanisms of gene regulation and its alterations in a disease context, in particular in cancer. We develop computational methods to combine various omics datasets to characterize patient data at a molecular level, by performing primary data analysis as well as applying statistical methods to combine molecular and clinical data sources. These methods are increasingly used to include single cell datasets and provide computational methods to combine single cell and bulk datasets. We initiated the OpenLab Epigenomics, which provides ready-to-use pipelines for processing of various NGS datasets as well as expertise and assistance.
Recent projects include a comprehensive characterisation of a large neuroblastoma patient cohort using epigenomic data from patients as well as single cell data. By combining multiple data sets, we identified multiple molecular signatures within patients corresponding to distinct clinical outcomes. In parallel, we are working on methods to combine single cell and bulk datasets allowing to reinterpret bulk datasets in the light of the cellular resolution of single cell datasets. This is done using methods based on matrix-factorisation which we are currently developing. In particular, these methods are well suited for the combination of distinct data types and enable to identify common signatures and data specific signatures. At a patient level, we are involved in a large consortium focusing on the study of comorbidities in schizophrenia patients and the molecular stratification of patient with mental disorders.
We are involved in a large consortium focusing on the study of comorbidities in schizophrenia patients and the molecular stratification of patient with mental disorders. This is done by applying a transfer learning strategy to jointly learn signatures from multiple, distributed cohorts with non-overlapping data types. At the same time, these signatures are compared to those derived from cohorts of patients with T2D or cardiovascular diseases to highlight commonalities and specific mechanisms.
We are applying computational methods in datasets related to HIV or HCV infection to describe the response of the host cell to infection both at transcriptional and regulatory level by combining scRNA-seq and scATAC-seq. We are using these two data types to reconstruct the regulatory networks and identify master regulators driving these processes.
Carl Herrmann is an engineer and physicist by training. He graduated in theoretical physics and was assistant-professor in Bioinformatics at the University Marseille before moving to Heidelberg University in 2012.
Dr. Carl Herrmann
Group leader at BioQuant-Zentrum
Kumar S.*, Warrel J.*, Shantao L., McGillivray P., Meyerson W., Salichos L., Harmanci, A., Martinez-FGundichely, A., Chan, C. W. Y., Nielsen, M. M., Locjovsky, L., Zhang, Y., Li, X., Pedersen, J. S., Herrmann C., Getz G., Khurana E. & Gerstein M. B.§ (2018). Passenger mutations in 2500 cancer genomes: Overall molecular functional impact and consequences, Cell, in Press, bioRxiv, doi: 10.1101/280446
Liu, L.*, Liu, C.*, Quintero, A.*, Wu, L*., Yuan, Y.*, Wang, M., Cheng, M., Leng, L., Xu, L., Dong, G., Li, R., Liu, Y., Wei, X., Xu, J., Chen, X., Lu, H., Chen, D., Wang, Q., Zhou, Q., Lin, X., Li, G., Liu, S., Wang, Q., Wang, H., Fink, J.L., Gao, Z., Liu, X., Hou, Y., Zhu, S., Yang, H., Ye, Y., Lin, G., Chen, F., Herrmann, C., Eils, R.§, Shang, Z.§ & Xu, X.§ (2019). Deconvolution of single-cell multi-omics layers reveals regulatory heterogeneity. Nature Communications, 10(1), 470. doi: 10.1038/s41467-018-08205-7
Chan, C.W.Y., Gu, Z., Bieg, M., Eils, R. & Herrmann, C.§ (2019). Impact of cancer mutational signatures on transcription factor motifs in the human genome. BMC Medical Genomics, 12(1), 64. doi: 10.1186/s12920-019-0525-4
Bauer, T.*, Trump, S.*, Ishaque, N.*, Thurmann, L.*, Gu, L.*, Bauer, M.*, Bieg, M., Gu, Z.G., Weichenhan, D., Mallm, J.P., Roder, S., Herberth, G., Takada, E., Mucke, O., Winter, M., Junge, K.M., Grutzmann, K., Rolle-Kampczyk, U., Wang, Q., Lawerenz, C., Borte, M., Polte, T., Schlesner, M., Schanne, M., Wiemann, S., Georg, C., Stunnenberg, H.G., Plass, C., Rippe, K., Mizuguchi, J., Herrmann, C*., Eils, R.§ & Lehmann, I.§ (2016). Environment-induced epigenetic reprogramming in genomic regulatory elements in smoking mothers and their children. Molecular Systems Biology, 12(3). doi: 10.15252/msb.20156520
Peifer, M.*§, Hertwig, F.*, Roels, F.*, Dreidax, D.*, Gartlgruber, M.*, Menon, R., Krämer, A., Roncaioli, J.L., Sand, F., Heukmann J. M., Ikram, F., Ackermann, S., Engesser, A., Kahlert, Y., Altmüller, J., Nürnberg, P., Thierry-Mieg, J., Thierry-Mieg, D., Mariappan, A., Heynck, S., Mariotti, E., Henrich, K.-O., Gloeckner, C., Bosco, G., Leuscher, I., Schweiger, M. R., Savelyeya, L., Watkins, S. C., Shao, C., Bell, E., Höfer, T., Achter, V., Lang, U., Theissen, J., Volland, R., Saadati, M., Eggert, A., de Wilde, B., Peng, Z., Zhao, C., Shi, L., Ortmann, M., Büttner, R., Perner, S., Hero, B., Schramm, A., Schulte, J. H., Herrmann C., O’Sullivan R., Westermann F.§, Thomas R. K.§ & Fischer M.§ (2015). Telomerase activation by genomic rearrangements in high-risk neuroblastoma. Nature, 526(7575), 700–704. doi: 10.1038/nature14980
*these authors contributed equally
§corresponding author
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