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pro vyhledávání: '"Anthony Baptista"'
Autor:
Anthony Baptista, Alessandro Barp, Tapabrata Chakraborti, Chris Harbron, Ben D. MacArthur, Christopher R. S. Banerji
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)
Abstract Deep neural networks (DNNs) are powerful tools for approximating the distribution of complex data. It is known that data passing through a trained DNN classifier undergoes a series of geometric and topological simplifications. While some pro
Externí odkaz:
https://doaj.org/article/97e8c4f8b80743829e934cc3478f8c28
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-14 (2024)
Abstract Complex biological processes, such as cellular differentiation, require intricate rewiring of intra-cellular signalling networks. Previous characterisations revealed a raised network entropy underlies less differentiated and malignant cell s
Externí odkaz:
https://doaj.org/article/e0128e2e8e774f77a26841625fa62c15
Publikováno v:
BMC Bioinformatics, Vol 25, Iss 1, Pp 1-19 (2024)
Abstract Background Biological networks have proven invaluable ability for representing biological knowledge. Multilayer networks, which gather different types of nodes and edges in multiplex, heterogeneous and bipartite networks, provide a natural w
Externí odkaz:
https://doaj.org/article/9f1e34c21ed543a08beaa9d321659347
Publikováno v:
Communications Physics, Vol 5, Iss 1, Pp 1-9 (2022)
With the amount of data available growing at exponential rates, methods based on networks have become a key tool for their investigation. The authors propose a framework to the study multilayer networks using a random walks with restart (RWR) method,
Externí odkaz:
https://doaj.org/article/74101f989ec14b688d6ea3cfde7c6f9b
Publikováno v:
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
Communications Physics
Communications Physics, 2022, 5 (1), pp.170. ⟨10.1038/s42005-022-00937-9⟩
Communications Physics, Nature Research, 2022, 5 (1), pp.170. ⟨10.1038/s42005-022-00937-9⟩
Universitat Politècnica de Catalunya (UPC)
Communications Physics
Communications Physics, 2022, 5 (1), pp.170. ⟨10.1038/s42005-022-00937-9⟩
Communications Physics, Nature Research, 2022, 5 (1), pp.170. ⟨10.1038/s42005-022-00937-9⟩
The amount and variety of data is increasing drastically for several years. These data are often represented as networks, which are then explored with approaches arising from network theory. Recent years have witnessed the extension of network explor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::98693a5c5dce5fe28a0e04c6bb077b81
https://hal.archives-ouvertes.fr/hal-03372495
https://hal.archives-ouvertes.fr/hal-03372495
Autor:
Anthony Baptista, Aurélien Perera
Publikováno v:
Journal of Chemical Physics
Journal of Chemical Physics, American Institute of Physics, 2019, 150 (6), pp.064504. ⟨10.1063/1.5066598⟩
Journal of Chemical Physics, American Institute of Physics, 2019, 150 (6), pp.064504. ⟨10.1063/1.5066598⟩
International audience; A two-component interaction model is introduced herein, which allows to describe macroscopic miscibility with various modes of tunable micro-segregation, ranging from phase separation to micro-segregation, and in excellent agr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5db115981e731bf9a097e22abd76a290
https://hal.archives-ouvertes.fr/hal-03093742/file/modelMH_revised.pdf
https://hal.archives-ouvertes.fr/hal-03093742/file/modelMH_revised.pdf