Microbial Genome
Microbial genome research focuses on understanding the structure, function, and evolution of microbial genomes, aiming to unlock insights into microbial diversity and their roles in various ecosystems. Current research heavily utilizes deep learning models, including transformer architectures and graph neural networks, to analyze genomic sequences, predict gene function, and perform tasks like metagenomic binning and haplotype assembly. These advancements are improving our ability to classify microbes, understand gene interactions, and even design new genetic sequences, with significant implications for medicine, biotechnology, and environmental science.
Papers
Defining Reference Sequences for Nocardia Species by Similarity and Clustering Analyses of 16S rRNA Gene Sequence Data
Manal Helal, Fanrong Kong, Sharon C. A. Chen, Michael Bain, Richard Christen, Vitali Sintchenko
Linear normalised hash function for clustering gene sequences and identifying reference sequences from multiple sequence alignments
Manal Helal, Fanrong Kong, Sharon C-A Chen, Fei Zhou, Dominic E Dwyer, John Potter, Vitali Sintchenko