- Andreas Bergthaler Group
- Christoph Binder Group
- Christoph Bock Group
- Sylvia Knapp Group
- Robert Kralovics Group
- Stefan Kubicek Group
- Joanna I. Loizou Group
- Jörg Menche Group
- Giulio Superti-Furga Group
- Georg Winter Group
- Chemical Screening, Proteomics and Metabolomics Facility
- Biomedical Sequencing Facility (BSF)
- Keiryn Bennett (Senior Researcher on Leave)
Principal Investigator and Head of Bioinformatics
Recent advances in high-throughput technologies have created exciting new opportunities for systematically investigating the molecular basis of human disease. CeMM researchers employ a broad range of powerful post-genomic technologies, from next-generation sequencing of genomes, epigenomes and transcriptomes, to high-throughput proteomics and chemical screening. Our group applies diverse computational approaches to help understand and interpret the large datasets derived from these technologies.
A particular focus is the application of tools and concepts from network theory to elucidate the complex machinery of interacting molecules that constitutes the basis of (patho-) physiological states. The overarching goal of the emerging field of ‘network medicine’ is to (i) provide conceptual insights into the network signatures that characterize diseases states and to (ii) translate these insights to novel bioinformatics tools for the analysis of molecular data. These tools cover a broad range of important challenges, from disease gene identification to tumor classification or drug discovery.
Jörg Menche studied physics in Leipzig, Recife and Berlin. He did his PhD with Reinhard Lipowsky at the Max-Planck-Institute for Colloids and Interfaces in Potsdam and was a postdoctoral fellow with Albert-László Barabási at Northeastern University and at the Center for Cancer Systems Biology at Dana Farber Cancer Institute in Boston. He joined CeMM in 2015.
J Menche, A Sharma, M Kitsak, SD Ghiassian, M Vidal, J Loscalzo, AL Barabási. Uncovering disease-disease relationships through the incomplete interactome. Science 347 (6224), 1257601; 2015. (abstract)
SD Ghiassian*, J Menche*, AL Barabási. A DiseAse MOdule Detection (DIAMOnD) algorithm derived from a systematic analysis of connectivity patterns of disease proteins in the human Interactome. PLoS Comput Biol 11(4): e1004120; 2015. (abstract)
A Sharma*, J Menche*, C Huang, T Ort, X Zhou, M Kitsak, N Sahni, D Thibault, L Voung, F Guo, N Gulbahce, F Baribaud, J Tocker, R Dobrin, E Barnathan, H Liu, RA Panettieri, KG Tantisira, W Qiu, BA Raby, EK Silverman, M Vidal, ST Weiss, AL Barabási. A disease module in the interactome explains disease heterogeneity, drug response and captures novel pathways and genes in asthma. Human Molecular Genetics, 24(11):3005-20; 2015. (abstract)
M Hawrylycz, J Miller, V Menon, D Feng, T Dolbeare, A Guillozet-Bongaarts, A Jegga, BJ Aronow, Chang-Kyu Lee, A Bernard, M Glasser, D Dierker, J Menche, F Collman, P Grange, K Berman, S Mihalas, Z Yao, L Stewart, AL Barabási, J Schulkin, J Phillips, L Ng, C Dang, D Haynor, A Jones, D Van Essen, C Koch, E Lein. Canonical Genetic Signatures of the Adult Human Brain. Nature Neuroscience 18: 1832–1844; 2015. (abstract)
T Rolland, M Taşan, B Charloteaux, SJ Pevzner, Q Zhong, N Sahni, S Yi, I Lemmens, C Fontanillo, R Mosca, A Kamburov, SD Ghiassian, X Yang, L Ghamsari, D Balcha, BE Begg, P Braun, M Brehme, MP Broly, AR Carvunis, D Convery-Zupan, R Corominas, J Coulombe-Huntington, E Dann, M Dreze, A Dricot, C Fan, E Franzosa, F Gebreab, BJ Gutierrez, MF Hardy, M Jin, S Kang, R Kiros, GN Lin, K Luck, A MacWilliams, J Menche, RR Murray, A Palagi, MM Poulin, X Rambout, J Rasla, P Reichert, V Romero, E Ruyssinck, JM Sahalie, A Scholz, AA Shah, A Sharma, Y Shen, K Spirohn, S Tam, AO Tejeda, SA Trigg, JC Twizere, K Vega, J Walsh, ME Cusick, Y Xia, AL Barabási, LM Iakoucheva, P Aloy, J De Las Rivas, J Tavernier, MA Calderwood, DE Hill, T Hao, FP Roth, M Vidal. A proteome-scale map of the human interactome network. Cell 159 (5), 1212-1226; 2014. (abstract)
XZ Zhou*, J Menche*, AL Barabási, A Sharma. Human symptoms–disease network. Nature Communications 5; 2014. (abstract)
[* equal contribution]