Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Decomposing the sources of SARS-CoV-2 fitness variation in the United States

20 Aug 2021

Abstract excerpt

The fitness of a pathogen is a composite phenotype determined by many different factors influencing growth rates both within and between hosts. Determining what factors shape fitness at the host population-level is especially challenging because both intrinsic factors like pathogen genetics and extrinsic factors such as host behavior influence between-host transmission potential. This challenge has been...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to COVID-19 epidemiological studies
Share to Evolution and Genetic Dynamics
Share to SARS-CoV-2 and COVID-19 Research

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Source

Identifiers

PMID: 34642604
DOI: 10.1093/ve/veab073

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 8 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Decomposing the sources of SARS-CoV-2 fitness variation in the United StatesPMID 34642604Read ↗

Investigating the evolutionary origins of the first three SARS-CoV-2 variants of concernSemantic proximity Read ↗

Genomic-epidemiological analysis of 15 million SARS-CoV-2 genomes reveals accelerated fitness gain of JN.1 lineage.Semantic proximity Read ↗

Biophysical principles predict fitness of SARS-CoV-2 variants.Semantic proximity Read ↗

Analysis of 6.4 million SARS-CoV-2 genomes identifies mutations associated with fitness.Semantic proximity Read ↗

Fitness effects of mutations to SARS-CoV-2 proteinsSemantic proximity Read ↗

Inferring selection effects in SARS-CoV-2 with Bayesian Viral Allele Selection.Semantic proximity Read ↗

Evaluating the effect of SARS-CoV-2 spike mutations with a linear doubly robust learner.Semantic proximity Read ↗

Prediction and evolution of the molecular fitness of SARS-CoV-2 variants: Introducing SpikeProSemantic proximity Read ↗

Prediction and Evolution of the Molecular Fitness of SARS-CoV-2 Variants: Introducing SpikePro.Semantic proximity Read ↗

Estimating the transmission advantage of the D614G mutant strain of SARS-CoV-2, December 2019 to June 2020Semantic proximity Read ↗

Estimation of SARS-CoV-2 fitness gains from genomic surveillance data without prior lineage classification.Semantic proximity Read ↗

Learning the fitness dynamics of pathogens from phylogeniesSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.