SB2CLab
Synthetic Biology and Biosystems Control Lab (SB2CL). 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
Web page: http://sb2cl.ai2.upv.es
Funding details: Related items
Projects: BioDynamics
Institutions: Universitat Politècnica de València
https://orcid.org/0000-0003-4144-3521
Jesús Picó is Full Professor of Automatic Control at The Department of Systems Engineering and Control of the Universitat Politècnica de València (UPV). In 2013 he created the Laboratory of Synthetic Biology and Biosystems Control (SB2CLab) of the Institute of Automation and Industrial Informatics (ai2) at the UPV, the first multidisciplinary lab in Spain integrating systems and control engineers, bioinformatics and biotechnologists. His research interests are in the application of systems ...
BIODYNAMICS approach will aim to demonstrate that multipurpose microbial cell factories based on a standardized, modular plug-andplay synthetic biology pipeline are a real possibility for quicker, cheaper and more effective bioproduction. To this end, we will develop novel hybrid (data-driven and mechanistic) modelling and characterization methods and tools for advanced metabolic engineering biology. In particular, it will consider the design, implementation and analysis of optimal synthetic ...
