Bin Shao

The paper introduces a modular framework for designing eukaryotic transcription factors by separating functional domains and using synthetic promoters to control gene regulation.

PlasmidGPT generates engineered plasmid sequences and predicts sequence attributes using a language model trained on 153k plasmid sequences.

TXpredict predicts microbial transcriptomes from annotated genomes, achieving high correlation and expanding analysis to uncharacterized genera.

This paper introduces EcoVAE, a generative deep learning model for predicting global species distributions, achieving high precision and outperforming traditional methods.

This paper introduces a long-context language model for bacteriophage genomes, capable of predicting gene functions and generating novel sequences.

Riboformer predicts context-dependent translation dynamics using deep learning, correcting artifacts and identifying sequence motifs affecting ribosome stalling.

This paper introduces a flow-FISH assay for high-throughput, in situ measurement of RNA degradation rates without RNA purification.