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Inferring causal molecular networks: empirical assessment through a community-based effort

S. Hill, L. Heiser, T. Cokelaer, M. Unger, N. Nesser, D. Carlin, Y. Zhang, A. Sokolov, E. Paull, C. Wong, K. Graim, A. Bivol, H. Wang, F. Zhu, B. Afsari, L. Danilova, A. Favorov, W. Lee, D. Taylor, C. Hu, B. Long, D. Noren, A. Bisberg, B. Afsari, R. Al-Ouran, B. Anton, T. Arodz, O. Sichani, N. Bagheri, N. Berlow, A. Bisberg, A. Bivol, A. Bohler, J. Bonet, R. Bonneau, G. Budak, R. Bunescu, M. Caglar, B. Cai, C. Cai, D. Carlin, A. Carlon, L. Chen, M. Ciaccio, T. Cokelaer, G. Cooper, C. Creighton, S. Daneshmand, A. de la Fuente, B. Di Camillo, L. Danilova, J. Dutta-Moscato, K. Emmett, C. Evelo, M. Fassia, A. Favorov, E. Fertig, J. Finkle, F. Finotello, S. Friend, X. Gao, J. Gao, J. Garcia-Garcia, S. Ghosh, A. Giaretta, K. Graim, J. Gray, R. Großeholz, Y. Guan, J. Guinney, C. Hafemeister, O. Hahn, S. Haider, T. Hase, L. Heiser, S. Hill, J. Hodgson, B. Hoff, C. Hsu, C. Hu, Y. Hu, X. Huang, M. Jalili, X. Jiang, T. Kacprowski, L. Kaderali, M. Kang, V. Kannan, M. Kellen, K. Kikuchi, D. Kim, H. Kitano, B. Knapp, G. Komatsoulis, H. Koeppl, A. Krämer, M. Kursa, M. Kutmon, W. Lee, Y. Li, X. Liang, Z. Liu, Y. Liu, B. Long, S. Lu, X. Lu, M. Manfrini, M. Matos, D. Meerzaman, G. Mills, W. Min, S. Mukherjee, C. Müller, R. Neapolitan, N. Nesser, D. Noren, T. Norman, B. Oliva, S. Opiyo, R. Pal, A. Palinkas, E. Paull, J. Planas-Iglesias, D. Poglayen, A. Qutub, J. Saez-Rodriguez, F. Sambo, T. Sanavia, A. Sharifi-Zarchi, J. Slawek, A. Sokolov, M. Song, P. Spellman, A. Streck, G. Stolovitzky, S. Strunz, J. Stuart, D. Taylor, J. Tegnér, K. Thobe, G. Toffolo, E. Trifoglio, M. Unger, Q. Wan, H. Wang, L. Welch, C. Wong, J. Wu, A. Xue, R. Yamanaka, C. Yan, S. Zairis, M. Zengerling, H. Zenil, S. Zhang, Y. Zhang, F. Zhu, Z. Zi, G. Mills, J. Gray, M. Kellen, T. Norman, S. Friend, A. Qutub, E. Fertig, Y. Guan, M. Song, J. Stuart, P. Spellman, H. Koeppl, G. Stolovitzky, J. Saez-Rodriguez, and S. Mukherjee. Nature Methods, 13 (4): 310--318 (22.02.2016)
DOI: 10.1038/nmeth.3773

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Michael Unger

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Other publications of authors with the same name

Inferring causal molecular networks: empirical assessment through a community-based effortS. Hill, L. Heiser, T. Cokelaer, M. Unger, N. Nesser, D. Carlin, Y. Zhang, A. Sokolov, E. Paull, C. Wong and 163 other author(s). Nature Methods, 13 (4): 310--318 (22.02.2016)Use Cases für sterile blickgesteuerte Mensch-Maschine-Interaktionskonzepte im digitalen Operatiionssaal.B. Glaser, M. Unger, T. Schellenberg, and T. Neumuth. CURAC, page 157-162. (2015)Estimation of 3D structure and camera calibration from images under noisy conditions.M. Unger. RWTH Aachen University, (2011)Robot-Assisted Image-Guided Interventions.M. Unger, J. Berger, and A. Melzer. Frontiers Robotics AI, (2021)Scalable inference of heterogeneous reaction kinetics from pooled single-cell recordingsC. Zechner, M. Unger, S. Pelet, M. Peter, and H. Koeppl. Nature Methods, 11 (2): 197--202 (12.01.2014)Uncertainties in the Magnetic Field of the Milky WayM. Unger, and G. Farrar. (07.07.2017)Design and validation of a medical robotic device system to control two collaborative robots for ultrasound-guided needle insertions.J. Berger, M. Unger, J. Keller, C. Reich, T. Neumuth, and A. Melzer. Frontiers Robotics AI, (2022)Gab's gar schon eLearning?H. Rohland, M. Unger, and F. Gahmig. Informatik in der DDR, volume T-3 of LNI, page 209-219. Gesellschaft für Informatik, Bonn, (2008)Optimal variational perturbations for the inference of stochastic reaction dynamics.C. Zechner, P. Nandy, M. Unger, and H. Koeppl. CDC, page 5336-5341. IEEE, (2012)Design and evaluation of an AR-based thermal imaging system for planning reconstructive surgeries.M. Unger, A. Hänel, C. Chalopin, and D. Halama. Int. J. Comput. Assist. Radiol. Surg., 19 (8): 1659-1666 (августа 2024)