22 results on '"Kosakovsky Pond S"'
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2. Windshield splatter analysis with the Galaxy metagenomic pipeline
3. FUBAR: A Fast, Unconstrained Bayesian AppRoximation for Inferring Selection
4. Inconsistencies in Estimating the Age of HIV-1 Subtypes Due to Heterotachy
5. Statistics and Truth in Phylogenomics
6. Phylogenetic Analysis of Population-Based and Deep Sequencing Data to Identify Coevolving Sites in the nef Gene of HIV-1
7. Evolutionary Fingerprinting of Genes
8. Detection of Mammalian Virulence Determinants in Highly Pathogenic Avian Influenza H5N1 Viruses: Multivariate Analysis of Published Data
9. Estimating selection pressures on HIV‐1 using phylogenetic likelihood models
10. A Maximum Likelihood Method for Detecting Directional Evolution in Protein Sequences and Its Application to Influenza A Virus
11. Evolutionary Model Selection with a Genetic Algorithm: A Case Study Using Stem RNA
12. Identification of a clade A HIV envelope immunogen from Protocol G that elicits neutralizing antibodies to tier 2 viruses.
13. Molecular modeling and phylogenetic analyses highlight the role of amino acid 347 of the N1 subtype neuraminidase in influenza virus host range and interspecies adaptation.
14. Stepwise Evolution and Exceptional Conservation of ORF1a/b Overlap in Coronaviruses.
15. Characterization of changes in the hemagglutinin that accompanied the emergence of H3N2/1968 pandemic influenza viruses.
16. No more business as usual: Agile and effective responses to emerging pathogen threats require open data and open analytics.
17. Characterizing the multiplicity of HIV founder variants during sexual transmission among MSM.
18. Identification of an HIV-1 clade A envelope that exhibits broad antigenicity and neutralization sensitivity and elicits antibodies targeting three distinct epitopes.
19. Correcting the bias of empirical frequency parameter estimators in codon models.
20. Benchmarking multi-rate codon models.
21. Windshield splatter analysis with the Galaxy metagenomic pipeline.
22. Comparison of immunogen designs that optimize peptide coverage: reply to Fischer et al.
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