Zobrazeno 1 - 10
of 1 108
pro vyhledávání: '"mechanistic models"'
Autor:
Marina Esteban-Medina, Víctor Manuel de la Oliva Roque, Sara Herráiz-Gil, María Peña-Chilet, Joaquín Dopazo, Carlos Loucera
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 23, Iss , Pp 1129-1143 (2024)
We introduce drexml, a command line tool and Python package for rational data-driven drug repurposing. The package employs machine learning and mechanistic signal transduction modeling to identify drug targets capable of regulating a particular disea
Externí odkaz:
https://doaj.org/article/91caf232f7c649bbae3a8cf7b2230cb7
Autor:
Juliano Sarmento Cabral, Alma Mendoza‐Ponce, André Pinto daSilva, Johannes Oberpriller, Anne Mimet, Julia Kieslinger, Thomas Berger, Jana Blechschmidt, Maximilian Brönner, Alice Classen, Stefan Fallert, Florian Hartig, Christian Hof, Markus Hoffmann, Thomas Knoke, Andreas Krause, Anne Lewerentz, Perdita Pohle, Uta Raeder, Anja Rammig, Sarah Redlich, Sven Rubanschi, Christian Stetter, Wolfgang Weisser, Daniel Vedder, Peter H. Verburg, Damaris Zurell
Publikováno v:
People and Nature, Vol 6, Iss 5, Pp 1716-1741 (2024)
Abstract Current approaches to project spatial biodiversity responses to climate change mainly focus on the direct effects of climate on species while regarding land use and land cover as constant or prescribed by global land‐use scenarios. However
Externí odkaz:
https://doaj.org/article/35bbfe6f4cc24faebe05717e4906341d
Autor:
Budiman Minasny, Toshiyuki Bandai, Teamrat A. Ghezzehei, Yin-Chung Huang, Yuxin Ma, Alex B. McBratney, Wartini Ng, Sarem Norouzi, Jose Padarian, Rudiyanto, Amin Sharififar, Quentin Styc, Marliana Widyastuti
Publikováno v:
Geoderma, Vol 452, Iss , Pp 117094- (2024)
Machine learning (ML) applications in soil science have significantly increased over the past two decades, reflecting a growing trend towards data-driven research addressing soil security. This extensive application has mainly focused on enhancing pr
Externí odkaz:
https://doaj.org/article/b96fd0fe95a043a689a5f2030a96a07f
Publikováno v:
Geoderma, Vol 448, Iss , Pp 116970- (2024)
Estimations of the patterns and controls of soil organic carbon (SOC) could provide instructive insights into the potential impact of future global change on soil carbon (C). In this work, we combined GeoDetector and random forest (RF) to estimate SO
Externí odkaz:
https://doaj.org/article/2f1fd3aa4a074ff8a7e1318bfb6e283a
Autor:
Ben Noordijk, Monica L. Garcia Gomez, Kirsten H. W. J. ten Tusscher, Dick de Ridder, Aalt D. J. van Dijk, Robert W. Smith
Publikováno v:
Frontiers in Systems Biology, Vol 4 (2024)
Both machine learning and mechanistic modelling approaches have been used independently with great success in systems biology. Machine learning excels in deriving statistical relationships and quantitative prediction from data, while mechanistic mode
Externí odkaz:
https://doaj.org/article/330e48d93cd647ec83f274ca3c660175
Publikováno v:
Petroleum, Vol 9, Iss 4, Pp 629-646 (2023)
The majority of published empirical correlations and mechanistic models are unable to provide accurate flowing bottom-hole pressure (FBHP) predictions when real-time field well data are used. This is because the empirical correlations and the empiric
Externí odkaz:
https://doaj.org/article/2c47ab82cec34d10aa1441674fb6e5a8
Autor:
Anna Niarakis, Marek Ostaszewski, Alexander Mazein, Inna Kuperstein, Martina Kutmon, Marc E. Gillespie, Akira Funahashi, Marcio Luis Acencio, Ahmed Hemedan, Michael Aichem, Karsten Klein, Tobias Czauderna, Felicia Burtscher, Takahiro G. Yamada, Yusuke Hiki, Noriko F. Hiroi, Finterly Hu, Nhung Pham, Friederike Ehrhart, Egon L. Willighagen, Alberto Valdeolivas, Aurelien Dugourd, Francesco Messina, Marina Esteban-Medina, Maria Peña-Chilet, Kinza Rian, Sylvain Soliman, Sara Sadat Aghamiri, Bhanwar Lal Puniya, Aurélien Naldi, Tomáš Helikar, Vidisha Singh, Marco Fariñas Fernández, Viviam Bermudez, Eirini Tsirvouli, Arnau Montagud, Vincent Noël, Miguel Ponce-de-Leon, Dieter Maier, Angela Bauch, Benjamin M. Gyori, John A. Bachman, Augustin Luna, Janet Piñero, Laura I. Furlong, Irina Balaur, Adrien Rougny, Yohan Jarosz, Rupert W. Overall, Robert Phair, Livia Perfetto, Lisa Matthews, Devasahayam Arokia Balaya Rex, Marija Orlic-Milacic, Luis Cristobal Monraz Gomez, Bertrand De Meulder, Jean Marie Ravel, Bijay Jassal, Venkata Satagopam, Guanming Wu, Martin Golebiewski, Piotr Gawron, Laurence Calzone, Jacques S. Beckmann, Chris T. Evelo, Peter D’Eustachio, Falk Schreiber, Julio Saez-Rodriguez, Joaquin Dopazo, Martin Kuiper, Alfonso Valencia, Olaf Wolkenhauer, Hiroaki Kitano, Emmanuel Barillot, Charles Auffray, Rudi Balling, Reinhard Schneider, the COVID-19 Disease Map Community
Publikováno v:
Frontiers in Immunology, Vol 14 (2024)
IntroductionThe COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use high-quality, mechanistic content describing SARS-CoV-2-host interactions and develop interoperable b
Externí odkaz:
https://doaj.org/article/ac53015acf3143cf9c3f232ae67ad161
Autor:
Amanda Souza Câmara, Martin Mascher
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 21, Iss , Pp 1084-1091 (2023)
Genetic information is stored in very long DNA molecules, which are folded to form chromatin, a similarly long polymer fibre that is ultimately organised into chromosomes. The organisation of chromatin is fundamental to many cellular functions, from
Externí odkaz:
https://doaj.org/article/9057ce4960344b85bab7db59f732941d
Publikováno v:
Royal Society Open Science, Vol 10, Iss 8 (2023)
The most extensively used mathematical models in epidemiology are the susceptible-exposed-infectious-recovered (SEIR) type models with constant coefficients. For the first wave of the COVID-19 epidemic, such models predict that at large times equilib
Externí odkaz:
https://doaj.org/article/45ebec185e5144f9b2bbf4552d12637a
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