Antimicrobial resistance (AMR) is a global health crisis that poses a great threat to modern
medicine. Effective prevention strategies are urgently required to slow the emergence and …

Denoising diffusion models embody a type of generative artificial intelligence that can be
applied in computer vision, natural language processing and bioinformatics. In this Review …

Enzyme turnover numbers (k cat) are key to understanding cellular metabolism, proteome
allocation and physiological diversity, but experimentally measured k cat data are sparse …

Abstract Design of de novo synthetic regulatory DNA is a promising avenue to control gene
expression in biotechnology and medicine. Using mutagenesis typically requires screening …

Genomics is advancing towards data-driven science. Through the advent of high-throughput
data generating technologies in human genomics, we are overwhelmed with the heap of …

In recent years, generative protein sequence models have been developed to sample novel
sequences. However, predicting whether generated proteins will fold and function remains …

Synthetic biology provides a new paradigm for life science research (“build to learn”) and
opens the future journey of biotechnology (“build to use”). Here, we discuss advances of …

Machine learning is increasingly integrated into clinical practice, with applications ranging
from pre-clinical data processing, bedside diagnosis assistance, patient stratification …

Significant progress has been made in the field of plant genomics, as demonstrated by the
increased use of high-throughput methodologies that enable the characterization of multiple …

With the development of high-throughput biology techniques and artificial intelligence, it has
become increasingly feasible to design and construct artificial biological parts, modules …