Zobrazeno 1 - 10
of 32
pro vyhledávání: '"Carlos Perales"'
Autor:
Alba Gonzalez-Franquesa, Pau Gama-Perez, Marta Kulis, Karolina Szczepanowska, Norma Dahdah, Sonia Moreno-Gomez, Ana Latorre-Pellicer, Rebeca Fernández-Ruiz, Antoni Aguilar-Mogas, Anne Hoffman, Erika Monelli, Sara Samino, Joan Miró-Blanch, Gregor Oemer, Xavier Duran, Estrella Sanchez-Rebordelo, Marc Schneeberger, Merce Obach, Joel Montane, Giancarlo Castellano, Vicente Chapaprieta, Wenfei Sun, Lourdes Navarro, Ignacio Prieto, Carlos Castaño, Anna Novials, Ramon Gomis, Maria Monsalve, Marc Claret, Mariona Graupera, Guadalupe Soria, Christian Wolfrum, Joan Vendrell, Sonia Fernández-Veledo, Jose Antonio Enríquez, Angel Carracedo, José Carlos Perales, Rubén Nogueiras, Laura Herrero, Aleksandra Trifunovic, Markus A. Keller, Oscar Yanes, Marta Sales-Pardo, Roger Guimerà, Matthias Blüher, José Ignacio Martín-Subero, Pablo M. Garcia-Roves
Publikováno v:
Redox Biology, Vol 54, Iss , Pp 102353- (2022)
Metabolic plasticity is the ability of a biological system to adapt its metabolic phenotype to different environmental stressors. We used a whole-body and tissue-specific phenotypic, functional, proteomic, metabolomic and transcriptomic approach to s
Externí odkaz:
https://doaj.org/article/ad594c8df2c8447b85a354bfb7fa6b81
Autor:
Álvaro Lahiguera, Petra Hyroššová, Agnès Figueras, Diana Garzón, Roger Moreno, Vanessa Soto‐Cerrato, Iain McNeish, Violeta Serra, Conxi Lazaro, Pilar Barretina, Joan Brunet, Javier Menéndez, Xavier Matias‐Guiu, August Vidal, Alberto Villanueva, Barbie Taylor‐Harding, Hisashi Tanaka, Sandra Orsulic, Alexandra Junza, Oscar Yanes, Cristina Muñoz‐Pinedo, Luís Palomero, Miquel Àngel Pujana, José Carlos Perales, Francesc Viñals
Publikováno v:
EMBO Molecular Medicine, Vol 12, Iss 6, Pp 1-23 (2020)
Abstract Mitochondrial metabolism and the generation of reactive oxygen species (ROS) contribute to the acquisition of DNA mutations and genomic instability in cancer. How genomic instability influences the metabolic capacity of cancer cells is never
Externí odkaz:
https://doaj.org/article/85fc4cae15594bc18ccb7a3706bee159
Autor:
Carlos Perales-González
Publikováno v:
Neural Processing Letters. 53:2067-2080
Ensemble approaches introduced in the Extreme Learning Machine (ELM) literature mainly come from methods that relies on data sampling procedures, under the assumption that the training data are heterogeneously enough to set up diverse base learners.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::72f3b7571a939c97bb423467fb61f23d
https://doi.org/10.1007/s11063-021-10492-z
https://doi.org/10.1007/s11063-021-10492-z
Autor:
Sergio Rodríguez-Arévalo, Sònia Abás, Marc Aragó, Juan Moreno-Felici, Petra Hyroššová, Jose Carlos Perales, Carles Galdeano, Tiziana Ginex, Francisco Javier Luque, Carmen Escolano
Publikováno v:
Proceedings, Vol 22, Iss 1, p 95 (2019)
Phosphoenolpyruvate carboxykinase (PEPCK) is a key enzyme in gluconeogenesis, catalyzingthe decarboxylation of oxaloacetate to phosphoenolpyruvate. [...]
Externí odkaz:
https://doaj.org/article/ddc82735154c401190f258956eb2a5bd
Autor:
Marc Aragó, Sergio Rodríguez-Arévalo, Petra Hyrossova, Juan Moreno, Sònia Abás, Agnès Figueras, Belén Pérez, Francesc Viñals, María Carmen Escolano, José Carlos Perales
Publikováno v:
Proceedings, Vol 22, Iss 1, p 79 (2019)
Phosphoenolpyruvate carboxykinase (PEPCK) is the key enzyme in gluconeogenesis/glyceroneogenesis, which catalyzes the decarboxylation of oxaloacetate to phosphoenolpyruvate. [...]
Externí odkaz:
https://doaj.org/article/8fbe6ed00984477a97d55c55f358737c
Akademický článek
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Autor:
Francisco Fernández-Navarro, David Becerra-Alonso, Carlos Perales-González, Mariano Carbonero-Ruz, Javier Pérez-Rodríguez
Publikováno v:
Neural Computing and Applications. 32:13805-13823
Extreme learning machine (ELM) has shown to be a suitable algorithm for classification problems. Several ensemble meta-algorithms have been developed in order to generalize the results of ELM models. Ensemble approaches introduced in the ELM literatu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::39523c354514cf1831191fce63428a07
https://doi.org/10.1007/s00521-020-04788-9
https://doi.org/10.1007/s00521-020-04788-9
Publikováno v:
48th Euromicro Conference on Software Engineering and Advanced Applications (SEAA), 426-433
STARTPAGE=426;ENDPAGE=433;TITLE=48th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)
STARTPAGE=426;ENDPAGE=433;TITLE=48th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)
Sustainability is an increasingly-studied topic in software engineering in general, and in software architecture in particular. There are already a number of secondary studies addressing sustainability in software engineering, but no such study focus
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1f95e5119a8840e456a91ccc8b614748
https://research.rug.nl/en/publications/62fc0427-4666-4c6d-9196-28940d6eec4e
https://research.rug.nl/en/publications/62fc0427-4666-4c6d-9196-28940d6eec4e
Autor:
Carlos Perales-González, Francisco Fernández-Navarro, Mariano Carbonero-Ruz, Javier Pérez-Rodríguez, David Becerra-Alonso
Publikováno v:
Neurocomputing. 361:196-211
Extreme Learning Machine (ELM) has proven to be an efficient and speedy algorithm for classification. In order to generalize the results of standard ELM, several ensemble meta-algorithms have been implemented. On this manuscript, we propose a hierarc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c4c1779748b168c8c472b35540b1d62a
https://doi.org/10.1016/j.neucom.2019.06.040
https://doi.org/10.1016/j.neucom.2019.06.040
Publikováno v:
Methods in molecular biology (Clifton, N.J.). 2282
Nucleic acid conjugates are promising drugs for treating gene-related diseases. Conjugating specific units like lipids, cell-penetrating peptides, polymers, antibodies, and aptamers either at the 3'- or 5'-termini of a siRNA duplex molecule has resul
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::d6e93e0d2cfc69d4008c6f8fe2e5625d
https://pubmed.ncbi.nlm.nih.gov/33928573
https://pubmed.ncbi.nlm.nih.gov/33928573