15
staff
6.77 M
funding*
35
projects & contracts*
*data from the last 5 years
Research
Projects
Publications
  • Pedreira, A.; Vázquez, J.A.; García, M.R. (2022) Kinetics of Bacterial Adaptation, Growth, and Death at Didecyldimethylammonium Chloride sub-MIC Concentrations Frontiers in Microbiology DOI:10.3389/fmicb.2022.758237
  • Ovalle, J.C.; Vilas, C.; Antelo, L.T. (2022) On the use of deep learning for fish species recognition and quantification on board fishing vessels Marine Policy DOI:10.1016/j.marpol.2022.105015
  • González, P.; Osorio, R.R.; Pardo, X.C.; Banga, J.R.; Doallo, R. (2022) An efficient ant colony optimization framework for HPC environments Applied Soft Computing Journal DOI:10.1016/j.asoc.2021.108058
  • Otero-Muras I; Banga JR (2021) Synthetic Gene Circuit Analysis and Optimization " Computational Methods in Synthetic Biology" Humana Press / Springer ISBN:978-1-0716-0822-7
  • Otero-Muras I; Banga JR (2021) Automated Biocircuit Design with SYNBADm " Synthetic Gene Circuits" Springer ISBN:978-1-0716-1031-2
Theses
  • TFM - Andrea Arribas Jimeno (26/09/2022) Aplicabilidad de la tecnología de imágenes hiperespectrales (HSI) como método no invasivo para la evaluación de la calidad del pescado UNIVERSIDAD DE SANTIAGO DE COMPOSTELA
  • TFM - Artai Rodríguez Moimenta (19/07/2020) Desarrollo de un modelo de corte mecanístico que permita describir un proceso de fermentación mixta Universidad de Vigo (UVigo)
  • TFG - Laura Honrubia Baamonde (11/07/2019) Optimization of Benzalkonium Chloride treatment in the disinfection of L. Monocytogenes in the Food Industry UNIVERSIDAD DE LLEIDA
  • TFM - Pablo de la Torre Fernández (20/09/2018) Modelado del proceso de fermenatición vínica: co-cultivo de especies no convencionales Universidade da Coruña
  • PhD - Alejandro López Núñez (18/07/2018) CONTRIBUTIONS TO MATHEMATICAL MODELLING AND NUMERICAL SIMULATION OF BIOFILMS UdC
Innovation
Contracts
Capabilities
Products
  • Software | BioPreDyn-bench: a suite of benchmark problems for dynamic modeling in systems biology

    BioPreDyn-Bench is a suite of benchmark problems for dynamic modeling in systems biology. Currently, it contains six challenging parameter estimation problems, which aspire to serve as reference test cases in this area. This set includes medium- and large-scale kinetic models of E.coli, S. cerevisiae, D. melanogaster, Chinese Hamster Ovary (CHO) cells and a generic signaling network. The level of description includes metabolism, transcription, signal transduction and development.

    More information here.

  • Prototype | iObserver: On-board electronic monitoring system for catch identification and quantification

    iObserver is an innovative monitoring device based on automated video monitoring coupled with artificial intelligence developments for visual recognition and quantification of the catches on board fishing vessels.

    iObserver implements a continuous image recording system adaptable to different fishing vessels and deep learning algorithms to automatically identify and quantify catches on board in real time.

    iObserver focuses mainly on developing algorithms for robust automatic species recognition and size estimation of fish transported on a conveyor belt. Trials have been performed on board Spanish oceanographic vessels and commercial vessels. With over 300 days at sea, iObserver was used in more than 1000 hauls and took more than 200,000 pictures, and 17 species have already been included in the system's catalogue.  

    For further information, please contact us by e-mail.

  • Software | MIDER: a toolbox for network inference using mutual information distance and entropy reduction

    MIDER (mutual information distance and entropy reduction) is a general purpose software tool for inferring network structures. It has been developed with biological networks in mind but can be applied to other areas.

    More information here.

     

  • Software | MEIGO: a multiplatform toolbox for Global Optimization using Metaheuristics

    MEIGO is a global optimization toolbox that includes a number of metaheuristic methods, as well as a Bayesian inference method for parameter estimation.

    More information here.

Team

More