ArticleGenes2011
Evolution and quantitative comparison of genome-wide protein domain distributions.
Article in Genes, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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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.
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
3 citing papers in PubMed.
- Fluostatins M-Q Featuring a 6-5-6-6 Ring Skeleton and High Oxidized A-Rings from Marine Streptomyces sp. PKU-MA00045.Marine drugs · 2018Article
- Correcting for differential transcript coverage reveals a strong relationship between alternative splicing and organism complexity.Molecular biology and evolution · 2014Article
- A domain-centric solution to functional genomics via dcGO Predictor.BMC bioinformatics · 2013Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The metabolic and regulatory capabilities of an organism are implicit in its protein content. This is often hard to estimate, however, due to ascertainment biases inherent in the available genome annotations. Its complement of recognizable functional protein domains and their combinations convey essentially the same information and at the same time are much more readily accessible, although protein domain models trained for one phylogenetic group frequently fail on distantly related sequences. Pooling related domain models based on their GO-annotation in combination with de novo gene prediction methods provides estimates that seem to be less affected by phylogenetic biases. We show here for 18 diverse representatives from all eukaryotic kingdoms that a pooled analysis of the tendencies for co-occurrence or avoidance of protein domains is indeed feasible. This type of analysis can reveal general large-scale patterns in the domain co-occurrence and helps to identify lineage-specific variations in the evolution of protein domains. Somewhat surprisingly, we do not find strong ubiquitous patterns governing the evolutionary behavior of specific functional classes. Instead, there are strong variations between the major groups of Eukaryotes, pointing at systematic differences in their evolutionary constraints.
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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.