Flu Mutation Explorer: an Interactive Platform for Mapping Host Adaptation Mutations in Influenza A Viruses
Mojsiejczuk, L.; Wright, D.; Gifford, R. J.; Peacock, T. P.; Robertson, D. L.; Hughes, J. L.; Goldhill, D. H.; Hutchinson, E.
Show abstract
A rapid expansion of influenza A virus (IAV) genome sequencing has transformed global surveillance but has also created major challenges for interpreting the biological significance of viral mutations, particularly amino acid replacements associated with host adaptation. Resources have been created to support mutation annotation and phylogenetic analysis, but there is a need for a tool that integrates experimentally derived phenotypic evidence with evolutionary context in a framework suitable for users without prior training in bioinformatics. Here, we present the Flu Mutation Explorer, an interactive web application that combines large-scale influenza phylogenies with a manually curated database of reported mammalian adaptation mutations, to enable the exploration and interpretation of IAV genetic variation. The underlying database comprises over 1.5 million publicly available IAV sequences and over 1000 mutations associated with mammalian adaptation. The Flu Mutation Explorer enables users to query protein sequences, visualise amino acid distributions across viral lineages, examine host-specific conservation patterns, and identify adaptation mutation with links to supporting literature. We include case studies which demonstrate the platforms use in assessing amino acid conservation at sites of interest and in rapidly identifying candidate mammalian adaptation mutations during the ongoing H5N1 panzootic. By integrating genomic, phylogenetic, and functional information into an intuitive interface, the Flu Mutation Explorer lowers the barriers to interpreting influenza sequences for specialists and non-specialists alike.
Matching journals
The top 2 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- Characterizing the countrywide epidemic spread of influenza A(H1N1)pdm09 virus in Kenya between 2009 and 2018 96%
- ViralRecall: A Flexible Command-Line Tool for the Detection of Giant Virus Signatures in Omic Data 95%
- Divergent influenza-like viruses of amphibians and fish support an ancient evolutionary association 95%
Similar papers in this journal
- Emergence and spread of SARS-CoV-2 variants from farmed mink to humans and back during the epidemic in Denmark, June-November 2020. 96%
- Australia as a global sink for the genetic diversity of avian influenza A virus 95%
- No more business as usual: agile and effective responses to emerging pathogen threats require open data and open analytics 95%
Similar papers in this journal
- Interactions among common non-SARS-CoV-2 respiratory viruses and influence of the COVID-19 pandemic on their circulation in New York City 93%
- Bridging Genomics and Clinical Medicine: RSVrecon Enhances RSV Surveillance with Automated Genotyping and Clinically-important Mutation Reporting 93%
- Nomenclature for tracking of genetic variation of seasonal influenza viruses 92%
Similar papers in this journal
- Future Sequon Finder - A novel approach for predicting future N-linked glycosylation sequons on viral surface proteins 97%
- Machine learning using intrinsic genomic signatures for rapid classification of novel pathogens: COVID-19 case study 94%
- Structural impact of synonymous mutations in six SARS-CoV-2 Variants of Concern 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.