Computational and synthetic biology

Group Leaders
Group Members
Computational and synthetic biology group

General research support

Postdoctoral Researchers

PhD Students


Our group is interested in applying techniques ranging from modern machine learning and computational structural biology to high-throughput experimental methods such as NGS-based screening, in order to understand how genetic variation affects biological phenotypes (reverse engineering), as well as to design DNA sequences that can generate desired phenotypes (forward engineering). Currently, we are studying how mutations affect heterologous gene expression and transcriptional regulation on microalgae.

Selected Publications

Lang, B.*, Yang, J.-S.*, Garriga-Canut, M.*, Speroni, S., Aschern, M., Gili, M., Hoffmann, T., Tartaglia, G.G., Maurer, S.P.
Matrix-screening reveals a vast potential for direct protein-protein interactions among RNA binding proteins
(2021) Nucleic Acids Research, 49 (12), pp. 6702-6721. 

Weber, M., Burgos, R., Yus, E., Yang, J.-S., Lluch-Senar, M., Serrano, L.
Impact of C-terminal amino acid composition on protein expression in bacteria
(2020) Molecular Systems Biology, 16 (5), art. no. e9208, . 

Park, S.V.*, Yang, J.-S.*, Jo, H., Kang, B., Oh, S.S., Jung, G.Y.
Catalytic RNA, ribozyme, and its applications in synthetic biology
(2019) Biotechnology Advances, 37 (8), art. no. 107452, . 

Yang J.S.*# Garriga-Canut M.*, Link N., Carolis C., Broadbent K., Beltran-Sastre V., Serrano L., Maurer S.P.#
rec-YnH enables simultaneous many-by-many detection of direct protein-protein and protein-RNA interactions
(2018) Nature Communications, 9(1):3747

Yus E.*, Yang J.S.*, Sogues A., Serrano L. 
A reporter system coupled with high-throughput sequencing unveils key bacterial transcription and translation determinants 
(2017) Nature Communications, 8(1):368