Description

SilicoLife designs optimised microorganisms and novel pathways for industrial biotechnology applications, based on artificial intelligence and metabolic engineering approaches, shortening the development time and costs of new highly effective processes for the production of specific target compounds such as chemicals, food ingredients or biopolymers.

Silicolife builds computational models of microbial cells and develops proprietary state-of-the-art algorithms to find the most efficient pathways between raw-material and end-product, enabling our clients to streamline the strain design process and explore non-intuitive pathway modifications, dramatically cutting down costs in their development programs and reducing laboratory experimentation.

Silicolife builds on the experience of an interdisciplinary team of experts in computer science, artificial intelligence, bioinformatics, systems biology and bioprocess engineering and cooperates with leading research institutions all over the world. Leading chemical, materials and synthetic biology companies have chosen Silicolife as development partner to maintain their market edge in increasingly competitive markets. Large multinationals and SMEs alike benefit from our high professional standards and lean structure that make possible to provide competitive and compelling tailor-made solutions.

Areas/Lines R+D+i

Cell factory design
The design of biosynthetic pathways for both natural and unnatural compounds can be performed by assembling partial pathways recruited from different species, by engineering existing pathways and by using engineered enzymes exploring the natural diversity of enzyme-catalyzed reactions across several species.

Industrial Intelligence
SilicoLife combines its metabolic engineering capabilities with innovative tools for the extraction and integration of knowledge to provide a rational support to the Industrial Biotechnology decision process, as in the selection of high value products or the most suitable hosts for specific production targets.

Most important R+D+i projects

@note (pronounced as ANote) is a Biomedical Text Mining platform that copes with major Information Retrieval and Information Extraction tasks.

EEA IAN-AF – Characterization of food consumption and physical activity in Portugal (2015-2016)

ERA-IB DeYeast Library – Designer yeast strain library optimized for metabolic engineering applications (2014-2017)

ERA-IB Dynamics – Dynamics analysis and optimization of industrial microorganisms under dynamic process conditions (2015-2018)

ERA-IB IPCRES – Integrated Process and Cell Refactoring Systems for Enhanced Industrial Biotechnology (2014-2017)

ERA-MBT Thermofactories – Thermophilic cell factories for efficient conversion of brown algae biomass to high-value chemicals (2016-2019)

FP7 BRIGIT – New tailor-made biopolymers produced from sugars obtained from lignocellulosic residues for flame retardancy highly demanding applications (2012-2016)

H2020 DD-DeCaF – Bioinformatics Services for Data-Driven Design of Cell Factories and Communities (2016-2020)

H2020 SHIKIFACTORY100 – Modular cell factories for the production of 100 compounds from the shikimate pathway (2019-2022)

Marie Curie ITN GlycoPar – Parasite Glycobiology and anti-parasitic strategies (2014-2017)

Marie Curie ITN PACMEN – Predictive and Accelerated Metabolic Engineering Network (2016-2020)

Marie Curie ITN Symbiosys – Systematic Models for Biological Systems Engineering Training Network (2015-2019)

OptFlux – metabolic engineering workbench
OptFlux is an open-source and modular software to support in silico metabolic engineering tasks.

Portugal2020 SISBI – Software to aid the Industrial Biotechnology decision process (2016-2019)

Contact

Phone: (+351)  253 070 273

Email: info@silicolife.com