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  • 1
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    A functional update of the Escherichia coli K-12 genome (2005)
    BioMed Central
    Details
    Publication Date: 2022-05-25
    Description: Author Posting. © 2001 Serres et al. The definitive version was published in Genome Biology 2 (2001): research0035.1–0035.7, doi:10.1186/gb-2001-2-9-research0035.
    Description: Background: Since the genome of Escherichia coli K-12 was initially annotated in 1997, additional functional information based on biological characterization and functions of sequence-similar proteins has become available. On the basis of this new information, an updated version of the annotated chromosome has been generated. Results: The E. coli K-12 chromosome is currently represented by 4,401 genes encoding 116 RNAs and 4,285 proteins. The boundaries of the genes identified in the GenBank Accession U00096 were used. Some protein-coding sequences are compound and encode multimodular proteins. The coding sequences (CDSs) are represented by modules (protein elements of at least 100 amino acids with biological activity and independent evolutionary history). There are 4,616 identified modules in the 4,285 proteins. Of these, 48.9% have been characterized, 29.5% have an imputed function, 2.1% have a phenotype and 19.5% have no function assignment. Only 7% of the modules appear unique to E. coli, and this number is expected to be reduced as more genome data becomes available. The imputed functions were assigned on the basis of manual evaluation of functions predicted by BLAST and DARWIN analyses and by the MAGPIE genome annotation system. Conclusions: Much knowledge has been gained about functions encoded by the E. coli K-12 genome since the 1997 annotation was published. The data presented here should be useful for analysis of E. coli gene products as well as gene products encoded by other genomes.
    Description: This work was supported by NIH grant RO1 RR07861, the NASA Astrobiology Institute grant NCC2-1054, grants from the Edward Mallinckrodt, Jr Foundation and the Sinsheimer Foundation, and NSF grants NSF DBI - 9984882 and NSF IIS - 9996304.
    Keywords: Escherichia coli K-12
    Repository Name: Woods Hole Open Access Server
    Type: Article
    Format: 89280 bytes
    Format: application/pdf
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  • 2
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    EGenBio : a data management system for evolutionary genomics and biodiversity (2006)
    BioMed Central
    Details
    Publication Date: 2022-05-25
    Description: From The Third Annual Conference of the MidSouth Computational Biology and Bioinformatics Society Baton Rouge, Louisiana. 2–4 March, 2006.
    Description: © 2006 Nahum et al; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
    Description: EGenBio is a system for manipulation and filtering of large numbers of sequences, integrating curated sequence alignments and phylogenetic trees, managing evolutionary analyses, and visualizing their output. EGenBio is organized into three conceptual divisions, Evolution, Genomics, and Biodiversity. The Genomics division includes tools for selecting pre-aligned sequences from different genes and species, and for modifying and filtering these alignments for further analysis. Species searches are handled through queries that can be modified based on a tree-based navigation system and saved. The Biodiversity division contains tools for analyzing individual sequences or sequence alignments, whereas the Evolution division contains tools involving phylogenetic trees. Alignments are annotated with analytical results and modification history using our PRAED format. A miscellaneous Tools section and Help framework are also available. EGenBio was developed around our comparative genomic research and a prototype database of mtDNA genomes. It utilizes MySQL-relational databases and dynamic page generation, and calls numerous custom programs.
    Description: This work was partly funded by the National Institutes of Health (R22/R33 Innovation and Development grant to David Pollock), the National Science Foundation (CBM2/EPSCOR), and the State of Louisiana (Biological Computation and Visualization Center, Governor's iotechnology Initiative, and startup funds to David Pollock).
    Repository Name: Woods Hole Open Access Server
    Type: Article
    Format: 358631 bytes
    Format: application/pdf
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