Yi‐Xin Huo

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

The paper uses a language model to design cis-regulatory elements for prokaryotes without experimental data, achieving high success rates in gene expression and promoter activity.

Chlomito removes organelle genome contamination from nuclear assemblies with high accuracy and efficiency, improving genome quality.

This study develops a deep learning model to generate nonrepetitive and diverse CRISPR sgRNAs with high activity, validated for gene editing and regulation in Bacillus subtilis.

PromoGen generates species-specific functional promoters using transfer-learning based deep learning, outperforming other models and showing experimental activity in Bacillus subtilis.

Chrom-pro is a toolkit for chromosome-level genome assembly and analysis that integrates SGS, TGS, and Hi-C data into an automated workflow, achieving high BUSCO scores and collinearity with reference genomes.

This paper introduces a tRNA modification-based strategy to identify amino acid overproducers in microbial hosts.

The paper presents a chromosome-level genome assembly of Azadirachta indica and identifies terpene biosynthesis expansion linked to gene duplication on chromosome 13.

The paper modifies Escherichia coli MG1655 to create a more efficient host strain for chemical production by inactivating DNA defense systems, resulting in higher transformation efficiency and plasmid stability.

This paper reviews strategies to improve triterpenoid biosynthesis in yeast by engineering enzymes and metabolism, achieving gram-scale production from milligram-scale levels.