ReviewPLoS computational biology2019
Protein ensembles link genotype to phenotype.
Review in PLoS computational biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
58 citing papers in PubMed, 99 citations in OpenAlex.
- From static structures to dynamic energy landscapes: the latest revolution in molecular biology.Current opinion in structural biology · 2026Review
- Spatial biology of crowded tumor cells: A new map for designing drug combinations.Current opinion in structural biology · 2026Review
- Navigating the uncharted: AI-driven advances in protein structure, dynamics, interactions and ligand interactions for understudied families.BioData mining · 2026Review
- Ligand-driven modulation of chaperone-cochaperone networks shapes proteostasis outcomes.Protein science : a publication of the Protein Society · 2026Article
- Dual-channel graph learning reveals similarity and complementarity in protein-protein interaction networks.PLoS computational biology · 2026Article
- Genetic Polymorphisms Associated with Lithium Response in Bipolar Disorder: An Integrative Review and In Silico Protein-Protein Interaction Analysis.Pharmaceuticals (Basel, Switzerland) · 2026Article
- Global genetic rewiring during compensatory evolution in the yeast polarity network.EMBO reports · 2026Article
- Proteomic aging clocks and the risk of mortality among long-term cancer survivors.Journal of the National Cancer Institute · 2026Article
- PTMs as molecular encoders: reprogramming chaperones into epichaperomes for network control in disease.Trends in biochemical sciences · 2025Review
- Tumors and their microenvironments: Learning from pediatric brain pathologies.Biochimica et biophysica acta. Reviews on cancer · 2025Review
- Structural biology in variant interpretation: Perspectives and practices from two studies.American journal of human genetics · 2025Review
- Advancing Molecular Simulations: Merging Physical Models, Experiments, and AI to Tackle Multiscale Complexity.The journal of physical chemistry letters · 2025Review
- Pathogenic mutation impairs functional dynamics of Hsp60 in mono- and oligomeric states.Nature communications · 2025Article
- Analysis of Limited Proteolysis-Coupled Mass Spectrometry Data.Molecular & cellular proteomics : MCP · 2025Article
- Molecular principles underlying aggressive cancers.Signal transduction and targeted therapy · 2025Review
- Systems-Level Interactome Mapping Reveals Actionable Protein Network Dysregulation Across the Alzheimer's Disease Spectrum.Research square · 2025Article
- Allosteric modulation of NF1 GAP: Differential distributions of catalytically competent populations in loss-of-function and gain-of-function mutants.Protein science : a publication of the Protein Society · 2025Article
- CXCL14 in prostate cancer: complex interactions in the tumor microenvironment and future prospects.Journal of translational medicine · 2025Review
- Understanding the characteristic behaviour of the wild-type and mutant structure of FLT3 protein by computational methods.Computational and structural biotechnology journal · 2025Article
- Single nucleotide polymorphisms ofAnimal biotechnology · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 2 countries.
Funding
Abstract
Classically, phenotype is what is observed, and genotype is the genetic makeup. Statistical studies aim to project phenotypic likelihoods of genotypic patterns. The traditional genotype-to-phenotype theory embraces the view that the encoded protein shape together with gene expression level largely determines the resulting phenotypic trait. Here, we point out that the molecular biology revolution at the turn of the century explained that the gene encodes not one but ensembles of conformations, which in turn spell all possible gene-associated phenotypes. The significance of a dynamic ensemble view is in understanding the linkage between genetic change and the gained observable physical or biochemical characteristics. Thus, despite the transformative shift in our understanding of the basis of protein structure and function, the literature still commonly relates to the classical genotype-phenotype paradigm. This is important because an ensemble view clarifies how even seemingly small genetic alterations can lead to pleiotropic traits in adaptive evolution and in disease, why cellular pathways can be modified in monogenic and polygenic traits, and how the environment may tweak protein function.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.