This site is under development. For the current active site, go to bcbhub.csic.es.

Research Group

Detalle de: Computational Biology Lab at MBG

Title Computational Biology Lab at MBG
Description

Our research is focused in computational systems and synthetic biology. We use mathematical modelling, simulation and optimization to understand complex biological systems and processes.

Current research topics include:

  • Reverse engineering: systems identification (dynamic modelling) of biological networks
  • Forward engineering: computer-aided design in synthetic biology
  • Optimality principles in biological systems
  • Dynamics and optimal control of biosystems
Home Page https://www.bangalab.org/
Contact Email j.r.banga@csic.es
Collaborating Companies
Spin Off
Patents
Hpc Resources
Institution MBG
Ontology Computational Methods, Artificial Intelligence, Machine Learning in Biology, Computational models and simulations, Biosystems Modeling, Gene regulatory networks, Metabolic modelling, High-performance Computing, Parallel Computing, Systems Biology, Microbial communities, Cloud Computing, Dynamical systems, Mathematical optimization, Synthetic biology
Tools saCeSS, MEIGO, AMIGO2: Advanced model identification using global optimization, GEARS, GenSSI 2.0, PREMER, VisId, SYNBADm, saCMM, saCeSS2, asynPDE
Service Units
Research Lines Reverse engineering: systems identification (dynamic modelling) of biological networks, Forward engineering: computer-aided design in synthetic biology, Optimality principles in biological systems, Dynamics and optimal control of biosystems
Funded Projects DATA-DRIVEN MECHANISTIC MODELLING, UNCERTAINTY QUANTIFICATION AND OPTIMISATION IN SYSTEMS BIOLOGY (DYNAMO-bio), ENHANCING THE COMPUTATIONAL BIOLOGY OF MICROORGANISMS AND PLANTS WITH NEW METHODS OF ARTIFICIAL INTELLIGENCE AND SUPERCOMPUTING (SuperBioComp), LARGE SCALE GLOBAL OPTIMIZATION IN SYSTEMS BIOLOGY (LarGO), DYNAMIC REGULATION ACROSS METABOLIC ENGINEERING SCALES. MULTI-MODEL INFERENCE AND DYNAMIC OPTIMALITY (BIODYNAMICS), Ensemble modelling in systems biology - from identification to uncertainty quantification in predictions and structure, Design, analysis and optimization of biochemical pathways and genetic regulatory networks using stochastic models, Generation of the CanPath prototype - a platform for predictive cancer pathway modeling, Systematic Models for Biological Systems Engineering Training Network, Design, characterization and optimal tuning of synthetic biocircuits for bioproduction with control of the metabolic load, Synthetic biology to improve bioprocesses: design, optimization, monitoring and control, From data to models: new bioinformatics methods and tools for data-driven predictive dynamic modelling in biotechnological applications, Network for integrated cellular homeostasis, Towards an understanding of dynamic transcriptional regulation at global scale in bacteria: a systems biology approach
Selected Publications
View all (213 more)
Researchers Julio Rodriguez Banga, Ana Paredes Vázquez, Andrea Polo Rodríguez, David Rodríguez Penas

Suggest changes

Spotted something outdated or wrong here? Let us know below and we'll take care of it.

← Return to Home