Zobrazeno 1 - 10
of 495
pro vyhledávání: '"Heider Dominik"'
Autor:
da Silva, Tiago, Silva, Eliezer, Ribeiro, Adèle, Góis, António, Heider, Dominik, Kaski, Samuel, Mesquita, Diego
Structure learning is the crux of causal inference. Notably, causal discovery (CD) algorithms are brittle when data is scarce, possibly inferring imprecise causal relations that contradict expert knowledge -- especially when considering latent confou
Externí odkaz:
http://arxiv.org/abs/2309.12032
Publikováno v:
In iScience 17 May 2024 27(5)
Autor:
Leite, Jean Michel R.S., Ribeiro, Adèle, Pereira, Jaqueline L., de Souza, Camila Alves, Heider, Dominik, Soler, Júlia M. Pavan, Mingroni-Netto, Regina Célia, Fisberg, Regina M., Rogero, Marcelo M., Sarti, Flavia M.
Publikováno v:
In Clinical Nutrition ESPEN October 2024 63:311-321
Autor:
Matschinske, Julian, Späth, Julian, Nasirigerdeh, Reza, Torkzadehmahani, Reihaneh, Hartebrodt, Anne, Orbán, Balázs, Fejér, Sándor, Zolotareva, Olga, Bakhtiari, Mohammad, Bihari, Béla, Bloice, Marcus, Donner, Nina C, Fdhila, Walid, Frisch, Tobias, Hauschild, Anne-Christin, Heider, Dominik, Holzinger, Andreas, Hötzendorfer, Walter, Hospes, Jan, Kacprowski, Tim, Kastelitz, Markus, List, Markus, Mayer, Rudolf, Moga, Mónika, Müller, Heimo, Pustozerova, Anastasia, Röttger, Richard, Saranti, Anna, Schmidt, Harald HHW, Tschohl, Christof, Wenke, Nina K, Baumbach, Jan
Machine Learning (ML) and Artificial Intelligence (AI) have shown promising results in many areas and are driven by the increasing amount of available data. However, this data is often distributed across different institutions and cannot be shared du
Externí odkaz:
http://arxiv.org/abs/2105.05734
Autor:
Ren, Yunxiao, Li, Carmen, Nanayakkara Sapugahawatte, Dulmini, Zhu, Chendi, Spänig, Sebastian, Jamrozy, Dorota, Rothen, Julian, Daubenberger, Claudia A., Bentley, Stephen D., Ip, Margaret, Heider, Dominik
Publikováno v:
In Computers in Biology and Medicine March 2024 171
Publikováno v:
In Computer Methods and Programs in Biomedicine December 2023 242
Publikováno v:
Bioinformatics 36(22-23) 2020 5514-5515
The generation of high-quality assemblies, even for large eukaryotic genomes, has become a routine task for many biologists thanks to recent advances in sequencing technologies. However, the annotation of these assemblies - a crucial step towards unl
Externí odkaz:
http://arxiv.org/abs/2009.03758
Autor:
Torkzadehmahani, Reihaneh, Nasirigerdeh, Reza, Blumenthal, David B., Kacprowski, Tim, List, Markus, Matschinske, Julian, Späth, Julian, Wenke, Nina Kerstin, Bihari, Béla, Frisch, Tobias, Hartebrodt, Anne, Hausschild, Anne-Christin, Heider, Dominik, Holzinger, Andreas, Hötzendorfer, Walter, Kastelitz, Markus, Mayer, Rudolf, Nogales, Cristian, Pustozerova, Anastasia, Röttger, Richard, Schmidt, Harald H. H. W., Schwalber, Ameli, Tschohl, Christof, Wohner, Andrea, Baumbach, Jan
Artificial intelligence (AI) has been successfully applied in numerous scientific domains. In biomedicine, AI has already shown tremendous potential, e.g. in the interpretation of next-generation sequencing data and in the design of clinical decision
Externí odkaz:
http://arxiv.org/abs/2007.11621
Publikováno v:
In Computational and Structural Biotechnology Journal December 2024 23:732-741
Improved Bevirimat resistance prediction by combination of structural and sequence-based classifiers
Autor:
Dybowski J Nikolaj, Riemenschneider Mona, Hauke Sascha, Pyka Martin, Verheyen Jens, Hoffmann Daniel, Heider Dominik
Publikováno v:
BioData Mining, Vol 4, Iss 1, p 26 (2011)
Abstract Background Maturation inhibitors such as Bevirimat are a new class of antiretroviral drugs that hamper the cleavage of HIV-1 proteins into their functional active forms. They bind to these preproteins and inhibit their cleavage by the HIV-1
Externí odkaz:
https://doaj.org/article/26d494233dd745a2b68e8c8a95535891