Bin‐Guang Ma

DDTRN predicts bacterial transcriptional regulatory networks from gene sequences using a dual descriptor model, achieving high AUROC and AUPR scores across multiple bacterial species.

PGBTR is a computational framework that uses CNN to predict bacterial transcriptional regulatory networks, outperforming existing methods on Escherichia coli and Bacillus subtilis datasets.

This paper develops a terminator strength prediction model and a GAN-based terminator sequence generator for E. coli, achieving high prediction accuracy and reliable sequence design.

This study investigates how Escherichia coli's chromosome structure and transcriptomic responses change under heat stress, revealing shifts in chromosome interactions and compactness.

This study uses 3C technology to analyze the 3D genome structure of Deinococcus radiodurans and shows UV irradiation alters chromosome conformation and gene expression.

This paper evaluates and classifies bacterial chromosome structure reconstruction tools using 3C/Hi-C and microscopy data, highlighting challenges and future directions.

This paper introduces EVRC, an algorithm for reconstructing chromosome 3D structures using co-clustering coefficients and error-vector resultant, showing high similarity to real structures in simulations and Hi-C data.

This study uses independent component analysis to identify transcriptional regulatory modules in Bradyrhizobium diazoefficiens USDA110, revealing insights into gene regulation and environmental adaptation.

This paper introduces a green-light activated CRISPRi system with a 40-fold dynamic range for precise gene repression in E. coli.

The paper investigates the spatial organization of bacterial transcriptional regulatory networks using chromatin interaction data from E. coli and B. subtilis, revealing stable spatial features under different conditions.

EVR reconstructs bacterial chromosome 3D structures from 3C/Hi-C data using an optimized algorithm for closed-loop features.

This study constructs the transcriptional regulatory network of Saccharomyces cerevisiae and analyzes its spatial organization in a 3D genome model, finding an optimized structure adapted to functional requirements.