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WIsH predicts the hosts of phages from their genomic sequences. It achieves 63% mean accuracy when predicting the host genus among 20 genera for 3 kbp-long phage contigs. WisH is also fast and accurate on phage sequences of a few kbp, makin

For PHAVES #23 next week (Oct 12 at 9AM CEST), Bjorn Criel, PhD student in Yves Briers’ group, the Laboratory of Applied Biotechnology, at Ghent University, will give a talk on PhaLP: A Database for the Study of Phage Lytic Proteins and The

For our next PHAVES (Tues, Oct 5 at 9AM CEST) we have Bjorn Criel, a PhD student in Yves Briers’ group, who will be talking about PhaLP: a database of Phage Lytic Proteins. Register for this and all upcoming seminars here!

For our next PHAVES (Tues, Oct 5 at 9AM CEST) we have Bjorn Criel, a PhD student in Yves Briers’ group, who will be talking about PhaLP: a database of Phage Lytic Proteins. Register for this and all upcoming seminars here!

Andrzej Zielezinski (Adam Mickiewicz University, Poland) and colleagues published a new preprint describing PHIST, a fast and accurate prediction of prokaryotic hosts from metagenomic viral sequences.

Michael Shamash (McGill University, Canada) and colleagues published a perspective in ISME Journal on phages in the infant gut. They propose a theoretical framework governing early childhood gut virome assembly and development, which depend

Michael Roach (Flinders University) and colleagues published a new paper in F1000 Research entitled Philympics: Prophage Predictions Perplex Programs. They present a library of gold-standard bacterial genome annotations that include manuall

Ricardo Pascal, a bioinformatics engineer in Denmark, is tracking the phage software ecosystem. Feel free to add a link or two to his list!

Christopher Turkington (University of California, Merced) and colleagues published a preprint on hafeZ, a tool able to identify ‘active’ prophages within bacterial genomes through genomic read mapping. They've applied hafeZ to publicly avai

Clément Coclet and Simon Roux (DOE Joint Genome Institute) published a review in Current Opinion in Virology on major challenges of host prediction methods for uncultivated phages. They highlight different approaches, giving their distinct

The Center for Phage Technology has published CPT-GFFParser, an extensively featured Python parser for GFF format reading/writing developed by the CPT bioinformatics team (main author Anthony Criscione). It's now available as a python packa

Carol Zhou (Lawrence Livermore National Laboratory) and colleagues published a new paper in G3 Genes|Genomes|Genetics entitled MultiPhATE2: Code for functional annotation and comparison of phage genomes.

PhageAI 0.7.2 has been released! What's new: Life cycle classifier v1.3 to distinguish between virulent and temperate phages (accuracy benchmark); PhageAI as free Python package on GitHub and PyPI; Duplicate samples detection alert in phag

The Center for Phage Technology (Texas A&M) has released its upgraded and improved Galaxy-Apollo phage annotation platform. This is a free, web-based, gold-standard system for phage annotation, and their website includes training materials

Vito Adrian Cantu (San Diego State University) and colleagues published a new preprint on Phage Artificial Neural Networks (PhANNs), a fast and accurate machine learning tool and web server that can classify phage proteins into ten major cl

Stanley Ho (University of Birmingham) has made a list of bioinformatics tools for predicting and identifying phages in metagenomes and metaviromes. See also this Twitter thread, where others have been sharing similar tools.

DBSCAN-SWA is a new tool for prophage detection, recently published as a preprint by Rui Gan (Harbin Institute of Technology, China) and colleagues. Preprint | Github.

Kristopher Kieft and colleagues (University of Wisconsin-Madison) published a new paper in Microbiome about VIBRANT, a new hybrid machine learning and protein similarity approach for automated recovery, annotation and curation of microbial

Anti-CRISPRs are widespread among phages, but it's been hard to screen for them. Jiawei Wang and colleagues at Monash University have developed an ensemble learning based predictor, PaCRISPR, to accurately identify anti-CRISPRs from protein

Dmitry Antipov (Institute for Translational Biomedicine, Russia) and colleagues published a new paper in Bioinformatics on metaviralSPAdes, a tool for viral assembly from metagenomic data.