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  GCsnap: Interactive Snapshots for the Comparison of Protein-Coding Genomic Contexts

Pereira, J. (2021). GCsnap: Interactive Snapshots for the Comparison of Protein-Coding Genomic Contexts. Journal of Molecular Biology, 433(11): 166943. doi:10.1016/j.jmb.2021.166943.

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Pereira, J1, Autor           
Affiliations:
1Department Protein Evolution, Max Planck Institute for Developmental Biology, Max Planck Society, ou_3375791              

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 Zusammenfassung: The biological function and evolutionary history of protein-coding genes are not only written in their nucleotide sequences. The comparison of genomic contexts throughout different lineages may highlight genomic mechanisms in the generation of new protein families, while the conservation of gene clusters may unravel, for instance, metabolic pathways. Various tools and databases exist that allow for the analysis and comparison of genomic contexts, but each has its own limitations. Online databases allow for quick comparisons, but only for those genomes for which data were pre-calculated. More advanced tools may allow for the comparison of any genome, but are often limited to a given phylogenetic kingdom or provide only a snapshot of the genomic contexts without further information about the genes involved. Here, we introduce GCsnap, a flexible Python-based tool that allows for the interactive comparison of the genomic contexts of protein-coding genes from any genome at any taxonomic level, integrating them with functional and structural information. By connecting the output to different protein databases, users can navigate through the different genomic contexts from a simple interactive platform, facilitating the further analysis of the contexts found. GCsnap is not limited to a single input format, can perform batch jobs and accepts protein classification maps. Results are stored in detailed, human and machine-readable files, and customizable, publication-ready figures. GCsnap is freely available from https://github.com/JoanaMPereira/GCsnap and can be set up easily on any computer.

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 Datum: 2021-05
 Publikationsstatus: Erschienen
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 Identifikatoren: DOI: 10.1016/j.jmb.2021.166943
PMID: 33737026
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Titel: Journal of Molecular Biology
  Andere : JMB
  Kurztitel : J. Mol. Biol.
Genre der Quelle: Zeitschrift
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Ort, Verlag, Ausgabe: Elsevier
Seiten: 8 Band / Heft: 433 (11) Artikelnummer: 166943 Start- / Endseite: - Identifikator: ISSN: 0022-2836
CoNE: https://pure.mpg.de/cone/journals/resource/0022-2836