Feng Ju

This study identifies a new PAO genus, Candidatus Dermatophostum, in wastewater treatment systems and proposes a ppk1-based classification framework for Dermatophilaceae PAOs.

Rider improves RNA virus discovery from metatranscriptomes by combining structure-informed screening with structural validation, outperforming existing tools and recovering divergent sequences.

The paper introduces SaprotHub, a platform that simplifies training and sharing of protein language models, enabling non-experts to build and collaborate on customized models.

This study reveals metabolic segregation of H2 and formate in anaerobic digestion consortia, showing their distinct roles in primary and secondary fermentation and highlighting functional gene clusters.

Evolla, a protein-language model, improves functional inference and discovers novel proteins through natural language queries and benchmarking.

This study analyzes RNA virus diversity in wastewater treatment plants, identifying new viral lineages and their ecological and health implications.

This study identifies a potent PVC-dechlorinating activity in gut microbiota of insect larvae using comparative metagenomics.

This study examines how climate warming affects soil antibiotic resistance genes and pathogenomes, finding increased mobility and risk of disease outbreaks.

This study shows that removing duplicate reads improves metagenomic assembly and binning yields and reduces computational costs in complex environmental samples.

FunGeneTyper is a deep learning framework for ultra-accurate classification and discovery of functional genes in microbiomes, outperforming existing methods in multiple environments.

M2IA is a web server that integrates microbiome and metabolome data to identify pathways linked to obesity using TwinsUK cohort data.

The paper develops a pipeline to predict cellulolytic competency in microbes by analyzing genome annotations and synergy machineries, identifying five groups based on carbohydrate active modules.