CeMM Adjunct Principal Investigator

Jörg Menche
Network Medicine

Professor
Institute of Mathematics of the University of Vienna
Dept. of Structural & Computational Biology at the Max Perutz Labs (MFPL)

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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.

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Biosketch

Jörg Menche studied physics in Leipzig, Recife and Berlin. During his PhD with Reinhard Lipowsky at the Max Planck Institute of Colloids and Interfaces in Potsdam he specialized in network theory. He then moved to Boston to work as a postdoctoral fellow with Albert-László Barabási at Northeastern University and at the Center for Cancer Systems Biology at Dana Farber Cancer Institute. In close collaboration with Joseph Loscalzo from Harvard Medical School and Marc Vidal from Dana Farber Cancer Institute, he applied tools and concepts from network theory to elucidate the complex machinery of interacting molecules that constitutes the basis of (patho-)physiological states. Jörg joined CeMM as Principal Investigator in 2015. He applies diverse computational approaches to help understand and interpret the large datasets derived from the broad range of powerful post-genomic technologies that CeMM researchers employ, from next-generation sequencing of genomes, epigenomes and transcriptomes, to high-throughput proteomics and chemical screening. Two major areas of interest of his group are network-based approaches to rare diseases and understanding the basic principles of drug-drug interactions. His research group is supported by a Vienna Research Groups for Young Investigators career integration grant by the Vienna Science and Technology Fund (WWTF).

Selected Papers

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Selected Papers

Caldera M, et al. Mapping the perturbome network of cellular perturbations. Nat Comm. 2019;10:5140. (abstract)

F Langhauser, AI Casas, VTV Dao, E Guney, J Menche, E Geuss, PWM Kleikers MG Lopez, AL, Barabási, C Kleinschnitz, HHHW Schmidt. A diseasome cluster-based drug repurposing of soluble guanylate cyclase activators from smooth muscle relaxation to direct neuroprotection. npj Systems Biology & Applications 4:8; 2018. (abstract)

Caldera M*, Buphamalai P*, et al. Interactome-based approaches to human disease. Curr Opin Syst Biol. 2017;3:88. (abstract)

J Menche*, E Guney*, A. Sharma, P.J. Branigan, M.J. Loza, F. Baribaud, R. Dobrin, A.-L. Barabási. Integrating personalized gene expression profiles into predictive disease-associated gene pool. npj Systems Biology & Applications 3:10; 2017. doi:10.1038/s41540-017-0009-0. (abstract)

E Guney, J Menche, M Vidal, AL Barabási. Network-based in silico drug efficacy screening. Nature Communications 7:10331, 2016. doi: 10.1038/ncomms10331. (abstract)

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]