ArticleBioinformatics (Oxford, England)2018
ProteomeVis: a web app for exploration of protein properties from structure to sequence evolution across organisms' proteomes.
Article in Bioinformatics (Oxford, England), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 4 papers.
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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.
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Who cites it
4 citing papers in PubMed.
- Avoidance of protein unfolding constrains protein stability in long-term evolution.Biophysical journal · 2021Article
- Universal Constraints on Protein Evolution in the Long-Term Evolution Experiment with Escherichia coli.Genome biology and evolution · 2021Article
- Protein Melting Temperature Cannot Fully Assess Whether Protein Folding Free Energy Underlies the Universal Abundance-Evolutionary Rate Correlation Seen in Proteins.Molecular biology and evolution · 2019Article
- Protein ensembles link genotype to phenotype.PLoS computational biology · 2019Review
Corrections and comments
- Erratum issued
Authors and funding
8 authors.
Funding
Abstract
Motivation: Protein evolution spans time scales and its effects span the length of an organism. A web app named ProteomeVis is developed to provide a comprehensive view of protein evolution in the Saccharomyces cerevisiae and Escherichia coli proteomes. ProteomeVis interactively creates protein chain graphs, where edges between nodes represent structure and sequence similarities within user-defined ranges, to study the long time scale effects of protein structure evolution. The short time scale effects of protein sequence evolution are studied by sequence evolutionary rate (ER) correlation analyses with protein properties that span from the molecular to the organismal level. Results: We demonstrate the utility and versatility of ProteomeVis by investigating the distribution of edges per node in organismal protein chain universe graphs (oPCUGs) and putative ER determinants. S.cerevisiae and E.coli oPCUGs are scale-free with scaling constants of 1.79 and 1.56, respectively. Both scaling constants can be explained by a previously reported theoretical model describing protein structure evolution. Protein abundance most strongly correlates with ER among properties in ProteomeVis, with Spearman correlations of -0.49 (P-value < 10-10) and -0.46 (P-value < 10-10) for S.cerevisiae and E.coli, respectively. This result is consistent with previous reports that found protein expression to be the most important ER determinant. Availability and implementation: ProteomeVis is freely accessible at http://proteomevis.chem.harvard.edu. Supplementary information: Supplementary data are available at Bioinformatics online.
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