- PhD. José Luís Capelo-Martínez
- PhD. Florentino Fdez-Riverola
- PhD. Daniel Glez-Peña
- Alberto Gutiérrez Jácome
- Hugo López-Fernández
- PhD. Eva Lorenzo Iglesias
- PhD. José Ramón Méndez Reboredo
- PhD. Reyes Pavón Rial
- PhD. Miguel Reboiro-Jato
Florentino Fdez-Riverola, PhD
The Next Generation Computer Systems Group (SING, Sistemas Informáticos de Nueva Generación) brings together a reduced number of researches with the aim of developing intelligent models and deploying them in real environments. The expertise of the members comes from different areas related with previous research in developing symbolic, connexionistic and hybrid AI systems, solving security problems, administration of networks, e-commerce, VoIP, implementation of web applications and developing systems working with documental data bases. The projects carried out by the SING group always follow a practical point of view, but taking into consideration the formal aspects needed in any research work. Indeed, most interesting techniques employed in previous works cope with the utilisation of case-based reasoning, artificial neural networks, fuzzy logic, rough sets, intelligent agents and multi-agent systems.
José Luís Capelo-Martínez, PhD
The current research and focus areas of the Bioscope Group include Bio-analytical applications for Protein Identification and Proteomics as well as in organic and inorganic nano-synthesis. Among others, they develop new approaches for in-gel and in-solution protein identification throughout ultra-fast protein digestion and mass spectrometry-based techniques, new strategies for tissue sample preparation prior Mass Spectrometry Imaging of endometriosis tissues and prostate cancer tissues, faster and more efficient sample preparation methods for identification and quantification of antidoping substances, new methods to identify doping abuse biomarkers by MALDI-TOF-MS and MALDI-TOF-TOF-MS, new methodologies for protein quantification by stable isotopic labelling techniques and mass spectroscopy, new methods for bacterial identification by MALDI-TOF-MS with application in disease screening and bioterrorism combat.
This work was partially funded by the INOU14-08 project from the University of Vigo.