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

Fitness Effects of Mutations: An Assessment of PROVEAN Predictions Using Mutation Accumulation Data.

Genome biology and evolution - 4 Jan 2022

Sandell Linnea, Sharp Nathaniel P

Abstract excerpt

Predicting fitness in natural populations is a major challenge in biology. It may be possible to leverage fast-accumulating genomic data sets to infer the fitness effects of mutant alleles, allowing evolutionary questions to be addressed in any organism. In this paper, we investigate the utility of one such tool, called PROVEAN. This program compares a query sequence with existing data to provide an...

Read the complete abstract on PubMed

Topics

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

Share to Alleles
Share to Biological Evolution
Share to Genetic Fitness

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Mutation

Share to Mutation Accumulation

Source

Open in PubMed Open full text

Identifiers

PMID: 35038732
DOI: 10.1093/gbe/evac004
PMCID: PMC8790079

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Fitness Effects of Mutations: An Assessment of PROVEAN Predictions Using Mutation Accumulation Data.PMID 35038732Read ↗

Viewing protein fitness landscapes through a next-gen lens.Semantic proximity Read ↗

The distribution of fitness effects of new mutations.Semantic proximity Read ↗

Quantifying and understanding the fitness effects of protein mutations: Laboratory versus nature.Semantic proximity Read ↗

Resolving Deleterious and Near-Neutral Effects Requires Different Pooled Fitness Assay Designs.Semantic proximity Read ↗

Estimating the Fitness Effects of New Mutations in the Wild Yeast Saccharomyces paradoxus.Semantic proximity Read ↗

Triallelic Population Genomics for Inferring Correlated Fitness Effects of Same Site Nonsynonymous Mutations.Semantic proximity Read ↗

Infer global, predict local: Quantity-relevance trade-off in protein fitness predictions from sequence data.Semantic proximity Read ↗

Fitness of Arabidopsis thaliana mutation accumulation lines whose spontaneous mutations are known.Semantic proximity Read ↗

Collateral fitness effects of mutation are not commonly caused by protein misfoldingSemantic proximity Read ↗

Enrich: software for analysis of protein function by enrichment and depletion of variants.Semantic proximity Read ↗

FiTMuSiC: Leveraging structural and (co)evolutionary data for protein fitness predictionSemantic proximity Read ↗

Genotype-fitness mapping of adaptive mutants reveals shifting low-dimensional structure across divergent environments.Semantic proximity Read ↗

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