SilicoLife leading DeepBio focused on the application of deep and machine learning to industrial biotechnology

SilicoLife, Univ of Minho and NOVA Univ of Lisbon were awarded a national grant for the development of novel approaches for the computational design of new molecules and biotransformations with enhanced capabilities, boosted by the use of methods and technologies from machine learning and deep learning.

The project DeepBio will focus on the development of new AI tools for the prediction of biological activities of relevant molecules, the generation of new molecular structures, reactions and metabolic pathways.

This new 3-year project, beginning this July, contributes to expand SilicoLife’s leadership in the use of AI methodologies in the industrial biotechnology context, promoting the development of computational solutions for tasks such as the prediction of the biological activities of relevant molecules for metabolic processes and their interactions, the generation of new molecules, reactions and metabolic pathways with specific activities, and the definition of new bioprocesses through enzyme optimization.

The application of deep learning methods will allow us to expand nature’s diversity combining the design of new-to-nature molecules with the creation of biological and sustainable routes to produce them” said Simão Soares, SilicoLife CEO. “This project is aligned with our efforts to transform industries leveraged on the combination of AI and biology”.

The project with a budget of six hundred thousand euro combines the industrial leadership of SilicoLife with the recognized research experience of the Centre of Biological Engineering (CEB) from University of Minho, and the Instituto de Tecnologia Química e Biológica António Xavier (ITQB-NOVA) from NOVA University of Lisbon. DeepBio is co-financed by Portugal 2020 (Norte2020 and Lisboa2020), the partnership agreement between Portugal and the European Commission for the promotion of policy economic, social and territorial development in the country.


Project: NORTE-01-0247-FEDER-039831 / LISBOA-01-0247-FEDER-039831

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