A decade ago, we had thousands of bacterial genomes. Now, we have millions. How to scale computational methods? Our paper in @naturemethods.bsky.social answers this: use evolutionary history to guide compression and search. rdcu.be/eg4OA w/ @baym.lol, @zaminiqbal.bsky.social et al. 🧵1/

Do you want to see a cool comparison of computational methods for reconstruction of human viral genomes? Check our latest preprint: doi.org/10.1101/2025... #Bioinformatics #Viruses

JARVIS3: an efficient encoder for genomic data doi.org/10.1093/bioi... #Bioinformatics #DataCompression

New from @dgpratas.bsky.social et al. for analyzing multiple sequences in multi-FASTA format using alignment-free methodologies. Scalable to millions of sequences for pandemic research and more AltaiR: a C toolkit for alignment-free and temporal analysis of multi-FASTA data doi.org/10.1093/giga...

Intra-host genomic diversity and integration landscape of human tissue-resident DNA virome doi.org/10.1093/nar/...

Machine Learning-Driven Discovery and Database of Cyanobacteria Bioactive Compounds: A Resource for Therapeutics and Bioremediation pubs.acs.org/doi/10.1021/... #Bioremediation #Bioinformatics

AltaiR: a C toolkit for alignment-free and temporal analysis of multi-FASTA data doi.org/10.1093/giga... #Bioinformatics #OpenScience