TeselaGen Biotechnology announced today the release of its Community Edition, a powerful, easy-to-use version of its popular Design Module within the TeselaGen® Operating System for biotechnology. The free, cloud-based software gives access to previously unavailable tools for designing DNA constructs.
TeselaGen Biotechnology announced today a two-year contract with BioMADE, the Department of Defense-sponsored bioindustrial Manufacturing Innovation Institute, to improve the informatics infrastructure around fermentation-based biomanufacturing. As part of this collaboration, TeselaGen will develop novel technologies that standardize data exchange, connect disparate software systems, and establish secure protocols to facilitate collaboration on AI-enabled projects.
TeselaGen Biotechnology announced today that it has partnered with the iGEM Foundation to support the iGEM Design League, a new competition that aims to advance synthetic biology, starting with Latin America. As part of the collaboration, students will have access to the TeselaGen® operating system for biotechnology to design projects that solve critical local problems using synthetic biology.
TeselaGen Biotechnology announced today a collaboration with the Agile BioFoundry (ABF) to lay the groundwork for deploying machine learning models on community-generated data to accelerate biomanufacturing and commercialization of bioproducts.
New functionality accelerates the design and development process, reducing R&D costs of biotherapeutics and vaccines
Collaboration and licensing agreement provide access to TeselaGen, the leading artificial-intelligence-enabled operating system for biotechnology
Collaboration deploys the TeselaGen AI-enabled operating system to close the gap between promising research and large-scale fermentation-based production of renewable bioproducts
LanzaTech and TeselaGen ink new 5-year deal to reduce the human carbon footprint using synthetic biology, extending their relationship through 2025
A collaboration between the Technical University of Denmark, Lawrence Berkeley National Laboratory, and TeselaGen Biotechnology, Inc. has shown that mechanistic and machine learning models can complement each other and can be combined to enable accurate genotype-to-phenotype predictions, and increase the productivity of important bioproducts produced by industrial organisms.
Ansa Biotechnologies Inc., the company developing a new way to make DNA using enzymes, is announcing a partnership with TeselaGen Biotechnology Inc., the company developing an integrated enterprise software operating system for designing, building, and optimizing biological and biochemical products.