Browse our latest Computational and Systems Biology articles

The novel pre-training framework integrating sequential and geometric encoders significantly enhances protein engineering by accurately predicting variant effects and thermostability, outperforming existing zero-shot learning methods with minimal computational cost.

Transcriptional regulatory network models can aid in identifying candidate genes associated with the target phenotype in bacterial genome-wide association studies.

SAVEMONEY is a computational tool that guides users to mix plasmids prior to nanopore sequencing, reducing the effective cost of whole-plasmid sequencing to below that of Sanger sequencing.