Collaborative work within iGEM to measure and characterize synthetic biology parts in an inter-laboratory study published in Nature Communication Biology.
Catedrático de Universidad
Profesor Titular de Universidad
Fernando Nobel Santos-Navarro
Welcome to the Synthetic Biology and Biosystems Control Lab (SB2CL) website. We focus our research on applications of systems engineering and control to Systems and Synthetic Biology, and Bioprocesses estimation and control. Our group is member of the Institute for Automatica and Industrial Informatics (ai2) at the Universitat Politècnica de València (Spain).
Our main interests are in:
- Dynamic regulation of gene expression for control of variability in gene expression and regulation of novel routes to obtain complex chemicals
Multi-objective optimization-based tuning of synthetic genetic circuits and its application to the standard characterization of parts and modules
- Machine learning for modeling and design of metabolic pathways. Automated workflows (Retropath), selection of enzymes (Selenzyme), design of DNA (promoters, RBS, etc) and optimal experimental design
- Machine learning based prediction of chemical diversity including the discovery of new bio-products and bioparts.
- Automation of the DBTL cycle. Protocol development for optimal process design biofabrication.
Analysis of metabolic networks using possibilistic methods and network theory for Metabolic Flux Analysis and Flux Balance Analysis
Sliding-mode observers and controllers for estimation and control in biosystems
Presenting at #IWBDA2020 showing how to improve metabolite production using model-based approach and optimization in #synbio @UPV @Institutoai2upv
Our new paper on biosensors and dynamic pathway regulation of cell factories is out in iScience a CellPress journal!