Sensing and computing with living cells usually means engineering them — rewiring genetic circuits, adding synthetic parts. It's powerful, but hard: metabolic burden, low
dAMN: Predicting Bacterial Growth Dynamics with a Hybrid Neural–Mechanistic Model
dAMN: Predicting Bacterial Growth Dynamics with a Hybrid Neural–Mechanistic Model
25 May 2026
Architecture of dAMN (figure from the original article). The model combines two neural networks — one predicting lag phase parameters, the other metabolic fluxes — within
RetroRules 2026: an expanded database combining biochemical and organic reaction templates, Nucleic Acid Research
RetroRules 2026: an expanded database combining biochemical and organic reaction templates, Nucleic Acid Research
15 December 2025
RetroRules (https://retrorules.org) is an open resource of reaction templates, which are generic reaction representations that describe the atomic transformations underlying
Microbial computing: Review and Perspectives, Biotechnology Advances
Microbial computing: Review and Perspectives, Biotechnology Advances
15 December 2025
Engineering microbial computers has been a longstanding endeavor in synthetic biology. Like other unconventional computing disciplines, the goal is to bring computation into
Reverse engineering molecules from fingerprints through deterministic enumeration and generative models, Journal of cheminformatics
Reverse engineering molecules from fingerprints through deterministic enumeration and generative models, Journal of cheminformatics
15 December 2025
Reverse engineering in molecular design aims to identify optimal structures based on activities, or properties, computed through molecular descriptors like fingerprints. This
Machine learning in predictive biocatalysis: A comparative review of methods and applications, Biotechnology Advances
Machine learning in predictive biocatalysis: A comparative review of methods and applications, Biotechnology Advances
26 September 2025
Harnessing Artificial Intelligence for Predictive BiocatalysisWe are advancing the field of predictive biocatalysis through cutting-edge machine learning approaches. Our team
An AI-driven Workflow for Accelerated Optimization of Cell-Free Protein Synthesis, iScience
An AI-driven Workflow for Accelerated Optimization of Cell-Free Protein Synthesis, iScience
26 September 2025
In a recently published article in iScience, researchers from the University of Paris-Saclay and the University of Lyon 1 have developed a software suite to optimize a cell-free
Constraint-based metabolic models have been used for decades to predict the phenotype of microorganisms in different environments. However, quantitative predictions are limited
The automated Galaxy-SynBioCAD pipeline for synthetic biology design and engineering, Nature Communications
The automated Galaxy-SynBioCAD pipeline for synthetic biology design and engineering, Nature Communications
30 August 2022
We believe that the synthetic biology and metabolic engineering communities need to be provided with easily acessible and usable computational tools enabling them to apply
Large scale active-learning-guided exploration for in vitro protein production optimization, Nature Communications
Large scale active-learning-guided exploration for in vitro protein production optimization, Nature Communications
24 April 2020
Cell-free lysates are a major platform for in vitro protein production but batch-to-batch variation makes production difficult to predict. A research team from the Micalis
RetroPath RL: Reinforcement Learning for Bioretrosynthesis, ACS Synthetic Biology
RetroPath RL: Reinforcement Learning for Bioretrosynthesis, ACS Synthetic Biology
24 April 2020
Metabolic engineering aims to produce chemicals of interest from living organisms, to advance toward greener chemistry. Despite efforts, the research and development process
Metabolic Perceptrons for Neural Computing in Biological Systems, Nature Communications
Metabolic Perceptrons for Neural Computing in Biological Systems, Nature Communications
29 August 2019
While machine learning methods are used in many areas, including human health, interfacing these methods with the living world has been little explored at the molecular level.
Optimizing Cell-Free Biosensors to Monitor Enzymatic Production, ACS Synthetic Biology
Optimizing Cell-Free Biosensors to Monitor Enzymatic Production, ACS Synthetic Biology
19 August 2019
Synthetic biology is the field of engineering biology inspired by engineering in computation, standardization, and construction to develop new devices composed of biological
RetroRules: A database of reaction rules for engineering biology, Nucleic Acids Research
RetroRules: A database of reaction rules for engineering biology, Nucleic Acids Research
3 October 2018
RetroRules is a database of reaction rules for metabolic engineering (). Reaction rules are generic descriptions of chemical reactions that can be used in retrosynthesis workflows
RetroPath2.0: A retrosynthesis workflow for metabolic engineers, Metab. Eng.
RetroPath2.0: A retrosynthesis workflow for metabolic engineers, Metab. Eng.
25 September 2017
Synthetic biology applied to industrial biotechnology is transforming the way we produce chemicals. However, despite advances in the scale and scope of metabolic engineering,
SensiPath: computer-aided design of sensing-enabling metabolic pathways, Nucleic Acids Research
SensiPath: computer-aided design of sensing-enabling metabolic pathways, Nucleic Acids Research
13 April 2016
Genetically-encoded biosensors offer a wide range of opportunities to develop advanced synthetic biology applications. Circuits with the ability of detecting and quantifying
Expanding Biosensing Abilities through Computer-Aided Design of Metabolic Pathways, ACS Synthetic Biology
Expanding Biosensing Abilities through Computer-Aided Design of Metabolic Pathways, ACS Synthetic Biology
1 April 2016
Detection of chemical signals is critical for cells in nature as well as in synthetic biology, where they serve as inputs for designer circuits. Important progress has been
Semi-supervised Gaussian Process for Automated Enzyme Search, ACS Synthetic Biology
Semi-supervised Gaussian Process for Automated Enzyme Search, ACS Synthetic Biology
24 March 2016
Synthetic biology is today harnessing the design of novel and greener biosynthesis routes for the production of added-value chemicals and natural products. The design of novel
Stereo Signature Molecular Descriptor, J Chem Info Model
Stereo Signature Molecular Descriptor, J Chem Info Model
5 April 2013
We present an algorithm to compute molecular graph descriptors considering the stereochemistry of the molecular structure based on our previously introduced signature molecular
A retrosynthetic biology approach to metabolic pathway design for therapeutic production, BMC Systems Biology
A retrosynthetic biology approach to metabolic pathway design for therapeutic production, BMC Systems Biology
5 August 2011
Retrosynthetic map connecting reachable compounds to E. coli metabolism (blue)Synthetic biology is used to develop cell factories for production of chemicals by constructively
↬ Welcome
Our group is interested in synthetic biology in whole-cell and cell-free systems. We develop computational and wet lab protocols to search, design, and engineer biological pathways and networks. Other activities include retrosynthesis, structure-activity, sequence-function relationships, and the design of experiments using active and reinforcement machine learning methods. The applications of our work include synthetic metabolic pathways and genetic circuits engineering for bioproduction, biosensing, and biocomputing.
↬ Open Position(s)
We have 2 Research Associate Open Position:
Seeking for a Research Associate Position in Synthetic Biology. Learn More.
Seeking for a Research Associate Position in Data Science / Systems Biology Biology. Learn More.
Interested in working with us? Don’t hesitate to contact us and share your CV!
