Xiaodong Fang

This study identifies a bacterial outer membrane protein as a substrate of a citrus protease, showing that protease activity reduces pathogen titers and delays disease symptoms in citrus.

SILO improves detection of disease susceptible variants in short IBD segments, outperforming existing models in simulated and real data.

This study identifies AGO10 as a key player in trans-species RNA interference in plant immunity, showing its role in pathogen gene silencing and immune response.

BioLLM integrates and benchmarks single-cell foundation models, revealing scGPTs' robust performance and highlighting limitations of scBERT in gene-level tasks.

This study reveals the structure of a hexameric phosphatase holoenzyme formed by a pathogen effector and host enzyme, showing enhanced stability and virulence function.

Pangaea improves metagenome assembly using short-reads with barcodes, achieving better contig continuity and more complete genomes than existing assemblers.

LRTK is a platform-agnostic toolkit for linked-read analysis of human genomes and metagenomes, offering simulation, alignment, variant calling, and taxonomic classification.

Deepurify uses a multi-modal deep language model with contrastive learning to improve MAG decontamination by leveraging genomic sequences and taxonomic lineages.

This paper benchmarks 15 de novo metagenome assembly tools on 32 datasets from various sequencing technologies, finding that long-read assemblers produce the highest contig continuity but miss some MAGs, while hybrid assemblers offer a balance of continuity and MAG completeness.

MetaTrass improves metagenome assembly by binning first and assembling later, producing more high-quality draft genomes from human gut microbiome samples.

Aquila_stLFR is a tool for diploid genome assembly and structural variant calling using stLFR linked-read data, achieving high sensitivity for deletions and specificity for insertions.

The paper introduces a hybrid algorithm combining BLAST, Smith-Waterman, and Needleman-Wunsch to predict eukaryotic protein subcellular localization, achieving high accuracy on two datasets.

This study identifies novel somatic mutations and altered mutation frequencies in Chinese colorectal cancer patients using whole exome sequencing, highlighting differences from TCGA data.