DNA data storage has the potential to enable extremely dense and stable information storage. However, parallel data access is challenging, to this end we develop temperature-responsive compartments that facilitate parallel and repeatable data access.
Synthetic biology drives the development of engineered mammalian cellular systems capable of novel/improved functions. The focus of this project involves fundamental research towards a
Single cells open opportunities for biotechnology and fundamental cell biology. However, individual plant cells isolated from tissues poorly survive and regenerate. We use materials from biomedical research and developmental regulators to alleviate this problem.
Poly-3-(R)-hydroxybutyrate (PHB) is a biobased polymer with different biological roles and biotechnological applications. In this project, we studied its accumulation in the bacteria Escherichia coli and Rhodospirillum rubrum under anaerobic conditions, combining different approaches.
Generating molecules from scratch with bespoke properties is one of the most challenging tasks in chemistry. In the past few years, generative deep learning has remarkably enhanced the field of de novo design, by allowing the generation of molecules with desired properties on demand.
AI has revolutionized drug discovery by enabling the efficient prediction of molecular properties essential for the development of new pharmaceuticals, such as bioactivity. In this context, machine learning can be used to prioritize vast chemical libraries, ranging from 103 to 109 molecular candidates. However, one of the biggest challenges to date is operating in the low-data regimes typical of drug discovery.