| BioTransformer: a comprehensive computational tool for small molecule metabolism prediction and metabolite identification Y Djoumbou-Feunang, J Fiamoncini, A Gil-de-la-Fuente, R Greiner, ... Journal of cheminformatics 11, 1-25, 2019 | 434 | 2019 |
| CEU mass mediator 3.0: a metabolite annotation tool A Gil-de-la-Fuente, J Godzien, S Saugar, R Garcia-Carmona, H Badran, ... Journal of proteome research 18 (2), 797-802, 2018 | 156 | 2018 |
| Knowledge-based metabolite annotation tool: CEU Mass Mediator AG de la Fuente, J Godzien, MF López, FJ Rupérez, C Barbas, A Otero Journal of pharmaceutical and biomedical analysis 154, 138-149, 2018 | 106 | 2018 |
| Recent developments along the analytical process for metabolomics workflows C Gonzalez-Riano, D Dudzik, A Garcia, A Gil-de-la-Fuente, A Gradillas, ... Analytical chemistry 92 (1), 203-226, 2019 | 100 | 2019 |
| Enhancing confidence of metabolite annotation in Capillary Electrophoresis-Mass Spectrometry untargeted metabolomics with relative migration time and in-source fragmentation M Mamani-Huanca, AG de la Fuente, A Otero, A Gradillas, J Godzien, ... Journal of Chromatography A 1635, 461758, 2021 | 36 | 2021 |
| Differentiating signals to make biological sense–A guide through databases for MS‐based non‐targeted metabolomics A Gil de la Fuente, E Grace Armitage, A Otero, C Barbas, J Godzien Electrophoresis 38 (18), 2242-2256, 2017 | 33 | 2017 |
| Unveiling the fragmentation mechanisms of modified amino acids as the key for their targeted identification M Mamani-Huanca, A Gradillas, A Gil de la Fuente, A López-Gonzálvez, ... Analytical Chemistry 92 (7), 4848-4857, 2020 | 28 | 2020 |
| Metabolite annotation and identification J Godzien, AG de la Fuente, A Otero, C Barbas Comprehensive analytical chemistry 82, 415-445, 2018 | 28 | 2018 |
| Integrating the potential of ion mobility spectrometry-mass spectrometry in the separation and structural characterisation of lipid isomers SM Camunas-Alberca, M Moran-Garrido, J Sáiz, A Gil-de-la-Fuente, ... Frontiers in Molecular Biosciences 10, 1112521, 2023 | 26 | 2023 |
| Probabilistic metabolite annotation using retention time prediction and meta-learned projections CA García, A Gil-de-la-Fuente, C Barbas, A Otero Journal of Cheminformatics 14 (1), 33, 2022 | 24 | 2022 |
| Characterization and annotation of oxidized glycerophosphocholines for non-targeted metabolomics with LC-QTOF-MS data AG de la Fuente, F Traldi, J Siroka, A Kretowski, M Ciborowski, A Otero, ... Analytica Chimica Acta 1037, 358-368, 2018 | 16 | 2018 |
| Recent developments in data acquisition, treatment and analysis with ion mobility‐mass spectrometry for lipidomics M Moran‐Garrido, SM Camunas‐Alberca, A Gil‐de‐la Fuente, A Mariscal, ... Proteomics 22 (15-16), 2100328, 2022 | 14 | 2022 |
| Processing metabolomics and proteomics data with open software DS Wishart, J Godzien, A Gil-de-la Fuente, R Mandal, R Rajabzadeh, ... Royal Society of Chemistry, 2020 | 14 | 2020 |
| Metabolomics DS Wishart, J Godzien, A Gil-de-la-Fuente, R Mandal, R Rajabzadeh, ... | 10 | 2020 |
| Hermite Polynomial Characterization of Heartbeats with Graphics Processing Units. A Gil, G Caffarena, DG Márquez, A Otero IWBBIO 13, 2014 | 9 | 2014 |
| Aspergillus Metabolome Database for Mass Spectrometry Metabolomics A Gil-De-La-Fuente, M Mamani-Huanca, MC Stroe, S Saugar, ... Journal of Fungi 7 (5), 387, 2021 | 7 | 2021 |
| LAS: A Lipid Annotation Service Capable of Explaining the Annotations It Generates M Fernández-López, A Gil-de-la-Fuente, J Godzien, FJ Rupérez, ... Computational and structural biotechnology journal 17, 1113-1122, 2019 | 6 | 2019 |
| Low-power, low-latency Hermite polynomial characterization of heartbeats using a field-programmable gate array K Lakhotia, G Caffarena, A Gil, DG Márquez, A Otero, MP Desai Bioinformatics and Biomedical Engineering: 4th International Conference …, 2016 | 5 | 2016 |
| GPU-Based Acceleration of ECG Characterization Using High-Order Hermite Polynomials A Gil, D G Márquez, G Caffarena, A Iriarte, A Otero Current Bioinformatics 11 (4), 430-439, 2016 | 3 | 2016 |
| Training Deep Learning Neural Networks for Predicting CCS Using the METLIN-CCS Dataset G Ramajo, C García, A Gil, A Otero International Work-Conference on Bioinformatics and Biomedical Engineering …, 2024 | 1 | 2024 |
Coral BarbasUniversidad San Pablo-CEUDirección de correo verificada de ceu.es
