Dr Gabriele Schweikert

Dr Gabriele Schweikert is a joint appointment between the Division of Computational Biology in the School and Cyber Valley in Tuebingen. Gabriele uses Machine Learning Tools to better understand important molecular processes in living cells, with a particular interest in epigenetic mechanisms. 

“All cells in our body share the same genetic code, the DNA. But what makes a liver cell a liver cell, what makes neurons communicate with other neurons, while white blood cells defend our body against germs and pathogens? Epigenetic mechanisms may provide the living cell with a system to efficiently use the specific information required for each cells’ specific needs,” Gabriele explained. “Currently, we have only limited understanding of its architecture and working, however, with modern high-throughput technologies we can register epigenomic snapshots of current states of cells. The data is very complex, high-dimensional, redundant and dynamic. A truly interdisciplinary approach is required that combines expert knowledge of epigenomic mechanisms with machine learning technologies. The impact of understanding these epigenetic processes holds immense promise for medical applications. For instance, malfunctioning of the epigenetic machinery are increasingly recognised as important contributors to tumourigenesis (e.g. in leukaemia).”

Selected Publications

• Lagger, S, Connelly, JC, Schweikert, G, Webb, S, Selfridge, J, Ramsahoye, BH, Yu, M, He, C, Sanguinetti, G, Sowers, LC, Walkinshaw, MD & Bird, A (2017) MeCP2 recognizes cytosine methylated tri-nucleotide and di-nucleotide sequences to tune transcription in the mammalian brain.  PLoS Genetics, vol. 13, no. 5, e1006793. https://doi.org/10.1371/journal.pgen.1006793
• Mayo, TR, Schweikert, G & Sanguinetti, G 2015, 'M 3 D: A kernel-based test for spatially correlated changes in methylation profiles', Bioinformatics, vol. 31, no. 6, pp. 809-816. https://doi.org/10.1093/bioinformatics/btu749
• Van Nues, R, Schweikert, G, De Leau, E, Selega, A, Langford, A, Franklin, R, Iosub, I, Wadsworth, P, Sanguinetti, G & Granneman, S (2017) Kinetic CRAC uncovers a role for Nab3 in determining gene expression profiles during stress.  Nature Communications, vol. 8, no. 1, 12. https://doi.org/10.1038/s41467-017-00025-5
• Varshney, D, Lombardi, O, Schweikert, G, Dunn, S, Suska, O & Cowling, V (2018) mRNA cap methyltransferase, RNMT-RAM, promotes RNA pol II-dependent transcription.  Cell Reports, vol. 23, no. 5, pp. 1530-1542.  https://doi.org/10.1016/j.celrep.2018.04.004