Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Sergio Picart-Armada"'
Autor:
Ozge Gurbuz, Gregorio Alanis-Lobato, Sergio Picart-Armada, Miao Sun, Christian Haslinger, Nathan Lawless, Francesc Fernandez-Albert
Publikováno v:
Frontiers in Genetics, Vol 13 (2022)
Indication expansion aims to find new indications for existing targets in order to accelerate the process of launching a new drug for a disease on the market. The rapid increase in data types and data sources for computational drug discovery has fost
Externí odkaz:
https://doaj.org/article/f4e2db66c554427080039e18a63f0ed6
Autor:
Jelena Weckerle, Sergio Picart-Armada, Stephan Klee, Tom Bretschneider, Andreas H. Luippold, Wolfgang Rist, Christian Haslinger, Holger Schlüter, Matthew J. Thomas, Bartlomiej Krawczyk, Francesc Fernandez-Albert, Marc Kästle, Daniel Veyel
Publikováno v:
Disease Models & Mechanisms, Vol 15, Iss 1 (2022)
Alterations in metabolic pathways were recently recognized as potential underlying drivers of idiopathic pulmonary fibrosis (IPF), translating into novel therapeutic targets. However, knowledge of metabolic and lipid regulation in fibrotic lungs is l
Externí odkaz:
https://doaj.org/article/fe96aab995ee466cbc2caa0fdb471e3f
Autor:
Sergio Picart-Armada, Francesc Fernández-Albert, Maria Vinaixa, Oscar Yanes, Alexandre Perera-Lluna
Publikováno v:
BMC Bioinformatics, Vol 19, Iss 1, Pp 1-9 (2018)
Abstract Background Pathway enrichment techniques are useful for understanding experimental metabolomics data. Their purpose is to give context to the affected metabolites in terms of the prior knowledge contained in metabolic pathways. However, the
Externí odkaz:
https://doaj.org/article/5d1df65c529e423a8c07bd1dac37b07e
Autor:
Sergio Picart-Armada, Steven J Barrett, David R Willé, Alexandre Perera-Lluna, Alex Gutteridge, Benoit H Dessailly
Publikováno v:
PLoS Computational Biology, Vol 15, Iss 9, p e1007276 (2019)
In-silico identification of potential target genes for disease is an essential aspect of drug target discovery. Recent studies suggest that successful targets can be found through by leveraging genetic, genomic and protein interaction information. He
Externí odkaz:
https://doaj.org/article/01d606f62d954bd9960910aea0304e90
Autor:
Sergio Picart-Armada, Francesc Fernández-Albert, Maria Vinaixa, Miguel A Rodríguez, Suvi Aivio, Travis H Stracker, Oscar Yanes, Alexandre Perera-Lluna
Publikováno v:
PLoS ONE, Vol 12, Iss 12, p e0189012 (2017)
Metabolomics experiments identify metabolites whose abundance varies as the conditions under study change. Pathway enrichment tools help in the identification of key metabolic processes and in building a plausible biological explanation for these var
Externí odkaz:
https://doaj.org/article/a68891daab274ad9b76d99ae1e8c8b4d
Autor:
Stephan Klee, Sergio Picart-Armada, Kathrin Wenger, Gerald Birk, Karsten Quast, Daniel Veyel, Wolfgang Rist, Coralie Violet, Andreas Luippold, Christian Haslinger, Matthew Thomas, Francesc Fernandez-Albert, Marc Kästle
Publikováno v:
American Journal of Physiology-Lung Cellular and Molecular Physiology. 324:L245-L258
The most common preclinical, in vivo model to study lung fibrosis is the bleomycin-induced lung fibrosis model in 2- to 3-mo-old mice. Although this model resembles key aspects of idiopathic pulmonary fibrosis (IPF), there are limitations in its pred
Autor:
Jorge Alejandro Lopera-Rodriguez, Martha Zuluaga, Sergio Picart-Armada, Alexandre Perera Lluna
Publikováno v:
2021 IEEE 2nd International Congress of Biomedical Engineering and Bioengineering (CI-IB&BI).
Publikováno v:
Journal of Chemical Information and Modeling
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
In silico analysis of biological activity data has become an essential technique in pharmaceutical development. Specifically, the so-called proteochemometric models aim to share information between targets in machine learning ligand–target activity
Autor:
Martin Hofmann-Apitius, Daniel Domingo-Fernández, Sarah Mubeen, Alexandre Perera-Lluna, Josep Marín-Llaó, Sergio Picart-Armada
Publikováno v:
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
Bioinformatics
Universitat Politècnica de Catalunya (UPC)
Bioinformatics
Summary High-throughput screening yields vast amounts of biological data which can be highly challenging to interpret. In response, knowledge-driven approaches emerged as possible solutions to analyze large datasets by leveraging prior knowledge of b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::480ebd7bb1b2f7a5ccd58d89ae68688d
https://publica.fraunhofer.de/handle/publica/265594
https://publica.fraunhofer.de/handle/publica/265594
Autor:
Sergio Picart-Armada, Samir Kanaan-Izquierdo, Maria Barranco-Altirriba, Jordi Fonollosa, Alexandre Perera-Lluna, Pol Solà-Santos
Publikováno v:
ANALYTICAL CHEMISTRY
r-IIB SANT PAU. Repositorio Institucional de Producción Científica del Instituto de Investigación Biomédica Sant Pau
instname
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
r-FSJD. Repositorio Institucional de Producción Científica de la Fundació Sant Joan de Déu
r-FSJD: Repositorio Institucional de Producción Científica de la Fundació Sant Joan de Déu
Fundació Sant Joan de Déu
r-IIB SANT PAU. Repositorio Institucional de Producción Científica del Instituto de Investigación Biomédica Sant Pau
instname
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
r-FSJD. Repositorio Institucional de Producción Científica de la Fundació Sant Joan de Déu
r-FSJD: Repositorio Institucional de Producción Científica de la Fundació Sant Joan de Déu
Fundació Sant Joan de Déu
Untargeted metabolomics using liquid chromatography coupled to mass spectrometry (LC-MS) allows the detection of thousands of metabolites in biological samples. However, LC-MS data annotation is still considered a major bottleneck in the metabolomics
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4c191b6f42679cbf9040c0383be5eb54
https://iibsantpau.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=4418
https://iibsantpau.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=4418