ArticlePloS one2022
Virtual 2D map of cyanobacterial proteomes.
Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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Who cites it
1 citing paper in PubMed, 1 citations in OpenAlex.
- Computational Analysis Predicts Correlations among Amino Acids in SARS-CoV-2 Proteomes.Biomedicines · 2023Article
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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cyanobacteria are prokaryotic Gram-negative organisms prevalent in nearly all habitats. A detailed proteomics study of Cyanobacteria has not been conducted despite extensive study of their genome sequences. Therefore, we conducted a proteome-wide analysis of the Cyanobacteria proteome and found Calothrix desertica as the largest (680331.825 kDa) and Candidatus synechococcus spongiarum as the smallest (42726.77 kDa) proteome of the cyanobacterial kingdom. A Cyanobacterial proteome encodes 312.018 amino acids per protein, with a molecular weight of 182173.1324 kDa per proteome. The isoelectric point (pI) of the Cyanobacterial proteome ranges from 2.13 to 13.32. It was found that the Cyanobacterial proteome encodes a greater number of acidic-pI proteins, and their average pI is 6.437. The proteins with higher pI are likely to contain repetitive amino acids. A virtual 2D map of Cyanobacterial proteome showed a bimodal distribution of molecular weight and pI. Several proteins within the Cyanobacterial proteome were found to encode Selenocysteine (Sec) amino acid, while Pyrrolysine amino acids were not detected. The study can enable us to generate a high-resolution cell map to monitor proteomic dynamics. Through this computational analysis, we can gain a better understanding of the bias in codon usage by analyzing the amino acid composition of the Cyanobacterial proteome.
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Registered trials
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