TY - JOUR A1 - Schimunek, Johannes A1 - Seidl, Philipp A1 - Elez, Katarina A1 - Hempel, Tim A1 - Le, Tuan A1 - Noé, Frank A1 - Olsson, Simon A1 - Raich, Lluís A1 - Winter, Robin A1 - Gokcan, Hatice A1 - Gusev, Filipp A1 - Gutkin, Evgeny M. A1 - Isayev, Olexandr A1 - Kurnikova, Maria G. A1 - Narangoda, Chamali H. A1 - Zubatyuk, Roman A1 - Bosko, Ivan P. A1 - Furs, Konstantin V. A1 - Karpenko, Anna D. A1 - Kornoushenko, Yury V. A1 - Shuldau, Mikita A1 - Yushkevich, Artsemi A1 - Benabderrahmane, Mohammed B. A1 - Bousquet-Melou, Patrick A1 - Bureau, Ronan A1 - Charton, Beatrice A1 - Cirou, Bertrand C. A1 - Gil, Gérard A1 - Allen, William J. A1 - Sirimulla, Suman A1 - Watowich, Stanley A1 - Antonopoulos, Nick A1 - Epitropakis, Nikolaos A1 - Krasoulis, Agamemnon A1 - Itsikalis, Vassilis A1 - Theodorakis, Stavros A1 - Kozlovskii, Igor A1 - Maliutin, Anton A1 - Medvedev, Alexander A1 - Popov, Petr A1 - Zaretckii, Mark A1 - Eghbal-Zadeh, Hamid A1 - Halmich, Christina A1 - Hochreiter, Sepp A1 - Mayr, Andreas A1 - Ruch, Peter A1 - Widrich, Michael A1 - Berenger, Francois A1 - Kumar, Ashutosh A1 - Yamanishi, Yoshihiro A1 - Zhang, Kam Y. J. A1 - Bengio, Emmanuel A1 - Bengio, Yoshua A1 - Jain, Moksh J. A1 - Korablyov, Maksym A1 - Liu, Cheng-Hao A1 - Marcou, Gilles A1 - Glaab, Enrico A1 - Barnsley, Kelly A1 - Iyengar, Suhasini M. A1 - Ondrechen, Mary Jo A1 - Haupt, V. Joachim A1 - Kaiser, Florian A1 - Schroeder, Michael A1 - Pugliese, Luisa A1 - Albani, Simone A1 - Athanasiou, Christina A1 - Beccari, Andrea A1 - Carloni, Paolo A1 - D’Arrigo, Giulia A1 - Gianquinto, Eleonora A1 - Goßen, Jonas A1 - Hanke, Anton A1 - Joseph, Benjamin P. A1 - Kokh, Daria B. A1 - Kovachka, Sandra A1 - Manelfi, Candida A1 - Mukherjee, Goutam A1 - Muñiz-Chicharro, Abraham A1 - Musiani, Francesco A1 - Nunes-Alves, Ariane A1 - Paiardi, Giulia A1 - Rossetti, Giulia A1 - Sadiq, S. Kashif A1 - Spyrakis, Francesca A1 - Talarico, Carmine A1 - Tsengenes, Alexandros A1 - Wade, Rebecca C. A1 - Copeland, Conner A1 - Gaiser, Jeremiah A1 - Olson, Daniel R. A1 - Roy, Amitava A1 - Venkatraman, Vishwesh A1 - Wheeler, Travis J. A1 - Arthanari, Haribabu A1 - Blaschitz, Klara A1 - Cespugli, Marco A1 - Durmaz, Vedat A1 - Fackeldey, Konstantin A1 - Fischer, Patrick D. A1 - Gorgulla, Christoph A1 - Gruber, Christian A1 - Gruber, Karl A1 - Hetmann, Michael A1 - Kinney, Jamie E. A1 - Padmanabha Das, Krishna M. A1 - Pandita, Shreya A1 - Singh, Amit A1 - Steinkellner, Georg A1 - Tesseyre, Guilhem A1 - Wagner, Gerhard A1 - Wang, Zi-Fu A1 - Yust, Ryan J. A1 - Druzhilovskiy, Dmitry S. A1 - Filimonov, Dmitry A. A1 - Pogodin, Pavel V. A1 - Poroikov, Vladimir A1 - Rudik, Anastassia V. A1 - Stolbov, Leonid A. A1 - Veselovsky, Alexander V. A1 - De Rosa, Maria A1 - De Simone, Giada A1 - Gulotta, Maria R. A1 - Lombino, Jessica A1 - Mekni, Nedra A1 - Perricone, Ugo A1 - Casini, Arturo A1 - Embree, Amanda A1 - Gordon, D. Benjamin A1 - Lei, David A1 - Pratt, Katelin A1 - Voigt, Christopher A. A1 - Chen, Kuang-Yu A1 - Jacob, Yves A1 - Krischuns, Tim A1 - Lafaye, Pierre A1 - Zettor, Agnès A1 - Rodríguez, M. Luis A1 - White, Kris M. A1 - Fearon, Daren A1 - Von Delft, Frank A1 - Walsh, Martin A. A1 - Horvath, Dragos A1 - Brooks III, Charles L. A1 - Falsafi, Babak A1 - Ford, Bryan A1 - García-Sastre, Adolfo A1 - Yup Lee, Sang A1 - Naffakh, Nadia A1 - Varnek, Alexandre A1 - Klambauer, Günter A1 - Hermans, Thomas M. T1 - A community effort in SARS-CoV-2 drug discovery JF - Molecular Informatics KW - COVID-19 KW - drug discovery KW - machine learning KW - SARS-CoV-2 Y1 - 2023 U6 - https://doi.org/https://doi.org/10.1002/minf.202300262 VL - 43 IS - 1 SP - e202300262 ER - TY - JOUR A1 - Gürler, A. A1 - Moll, Sebastian A1 - Weber, Marcus A1 - Meyer, Holger A1 - Cordes, Frank T1 - Selection and flexible optimization of binding modes from conformation ensembles JF - Biosystems Y1 - 2007 ER - TY - JOUR A1 - Guerler, A. A1 - Moll, Sebastian A1 - Weber, Marcus A1 - Meyer, Holger A1 - Cordes, Frank T1 - Selection and flexible optimization of binding modes from conformation ensembles JF - Biosystems Y1 - 2008 UR - http://www.sciencedirect.com/science/article/pii/S0303264707001670 U6 - https://doi.org/DOI: 10.1016/j.biosystems.2007.11.004 VL - 92 IS - 1 SP - 42 EP - 48 ER - TY - JOUR A1 - Senne, M. A1 - Trendelkamp-Schroer, B. A1 - Mey, A. A1 - Schütte, Christof A1 - Noé, Frank T1 - EMMA - A software package for Markov model building and analysis JF - Journal of Chemical Theory and Computation Y1 - 2012 U6 - https://doi.org/10.1021/ct300274u VL - 8 SP - 2223 EP - 2238 ER - TY - JOUR A1 - Frank, A. A1 - Chi Lau, L. A1 - Szabó, Jácint T1 - A note on degree-constrained subgraphs JF - Discrete Mathematics Y1 - 2008 VL - 308 IS - 12 SP - 2647 EP - 2648 PB - Elsevier ER - TY - JOUR A1 - Heinze, Rieke A1 - Dipankar, Anurag A1 - Henken, Cintia Carbajal A1 - Moseley, Christopher A1 - Sourdeval, Odran A1 - Trömel, Silke A1 - Xie, Xinxin A1 - Adamidis, Panos A1 - Ament, Felix A1 - Baars, Holger A1 - Barthlott, Christian A1 - Behrendt, Andreas A1 - Blahak, Ulrich A1 - Bley, Sebastian A1 - Brdar, Slavko A1 - Brueck, Matthias A1 - Crewell, Susanne A1 - Deneke, Hartwig A1 - Di Girolamo, Paolo A1 - Evaristo, Raquel A1 - Fischer, Jürgen A1 - Frank, Christopher A1 - Friederichs, Petra A1 - Göcke, Tobias A1 - Gorges, Ksenia A1 - Hande, Luke A1 - Hanke, Moritz A1 - Hansen, Akio A1 - Hege, Hans-Christian A1 - Hose, Corinna A1 - Jahns, Thomas A1 - Kalthoff, Norbert A1 - Klocke, Daniel A1 - Kneifel, Stefan A1 - Knippertz, Peter A1 - Kuhn, Alexander A1 - van Laar, Thriza A1 - Macke, Andreas A1 - Maurer, Vera A1 - Mayer, Bernhard A1 - Meyer, Catrin I. A1 - Muppa, Shravan K. A1 - Neggers, Roeland A. J. A1 - Orlandi, Emiliano A1 - Pantillon, Florian A1 - Pospichal, Bernhard A1 - Röber, Niklas A1 - Scheck, Leonhard A1 - Seifert, Axel A1 - Seifert, Patric A1 - Senf, Fabian A1 - Siligam, Pavan A1 - Simmer, Clemens A1 - Steinke, Sandra A1 - Stevens, Bjorn A1 - Wapler, Kathrin A1 - Weniger, Michael A1 - Wulfmeyer, Volker A1 - Zängl, Günther A1 - Zhang, Dan A1 - Quaas, Johannes T1 - Large-eddy simulations over Germany using ICON: a comprehensive evaluation JF - Quarterly Journal of the Royal Meteorological Society N2 - Large-eddy simulations (LES) with the new ICOsahedral Non-hydrostatic atmosphere model (ICON) covering Germany are evaluated for four days in spring 2013 using observational data from various sources. Reference simulations with the established Consortium for Small-scale Modelling (COSMO) numerical weather prediction model and further standard LES codes are performed and used as a reference. This comprehensive evaluation approach covers multiple parameters and scales, focusing on boundary-layer variables, clouds and precipitation. The evaluation points to the need to work on parametrizations influencing the surface energy balance, and possibly on ice cloud microphysics. The central purpose for the development and application of ICON in the LES configuration is the use of simulation results to improve the understanding of moist processes, as well as their parametrization in climate models. The evaluation thus aims at building confidence in the model's ability to simulate small- to mesoscale variability in turbulence, clouds and precipitation. The results are encouraging: the high-resolution model matches the observed variability much better at small- to mesoscales than the coarser resolved reference model. In its highest grid resolution, the simulated turbulence profiles are realistic and column water vapour matches the observed temporal variability at short time-scales. Despite being somewhat too large and too frequent, small cumulus clouds are well represented in comparison with satellite data, as is the shape of the cloud size spectrum. Variability of cloud water matches the satellite observations much better in ICON than in the reference model. In this sense, it is concluded that the model is fit for the purpose of using its output for parametrization development, despite the potential to improve further some important aspects of processes that are also parametrized in the high-resolution model. Y1 - 2017 U6 - https://doi.org/10.1002/qj.2947 VL - 143 IS - 702 SP - 69 EP - 100 ER - TY - JOUR A1 - Frank, M. A1 - von Kleist, Max A1 - Kunz, A. A1 - Harms, G. A1 - Schütte, Christof A1 - Kloft, Ch. T1 - Quantifying the impact of nevirapine-based prophylaxis strategies to prevent mother-to-child transmission of HIV-1 JF - Antimicrob. Agents Chemother. Y1 - 2011 UR - http://publications.imp.fu-berlin.de/1093/ VL - 55 IS - 12 SP - 5529 EP - 5540 ER - TY - GEN A1 - Bodlaender, Hans L. A1 - Koster, Arie M.C.A. A1 - Eijkhof, Frank van den A1 - Gaag, Linda C. van der T1 - Pre-processing for Triangulation of Probabilistic Networks N2 - The currently most efficient algorithm for inference with a probabilistic network builds upon a triangulation of a network's graph. In this paper, we show that pre-processing can help in finding good triangulations for probabilistic networks, that is, triangulations with a minimal maximum clique size. We provide a set of rules for stepwise reducing a graph, without losing optimality. This reduction allows us to solve the triangulation problem on a smaller graph. From the smaller graph's triangulation, a triangulation of the original graph is obtained by reversing the reduction steps. Our experimental results show that the graphs of some well-known real-life probabilistic networks can be triangulated optimally just by preprocessing; for other networks, huge reductions in their graph's size are obtained. T3 - ZIB-Report - 01-39 KW - triangulation KW - treewidth KW - probabilistic networks KW - pre-processing Y1 - 2001 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-6655 ER - TY - GEN A1 - Eijkhof, Frank van den A1 - Bodlaender, Hans L. A1 - Koster, Arie M.C.A. T1 - Safe reduction rules for weighted treewidth N2 - Several sets of reductions rules are known for preprocessing a graph when computing its treewidth. In this paper, we give reduction rules for a weighted variant of treewidth, motivated by the analysis of algorithms for probabilistic networks. We present two general reduction rules that are safe for weighted treewidth. They generalise many of the existing reduction rules for treewidth. Experimental results show that these reduction rules can significantly reduce the problem size for several instances of real-life probabilistic networks. T3 - ZIB-Report - 02-49 KW - weighted treewidth KW - preprocessing KW - probabilistic networks Y1 - 2002 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-7164 ER -