ArticleBMC bioinformatics2012
ANCAC: amino acid, nucleotide, and codon analysis of COGs--a tool for sequence bias analysis in microbial orthologs.
Article in BMC bioinformatics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 6 citations in OpenAlex.
- CompoDynamics: a comprehensive database for characterizing sequence composition dynamics.Nucleic acids research · 2022Article
- Aerobic prokaryotes do not have higher GC contents than anaerobic prokaryotes, but obligate aerobic prokaryotes have.BMC evolutionary biology · 2019Article
- Application of Subspace Clustering in DNA Sequence Analysis.Journal of computational biology : a journal of computational molecular cell biology · 2015Article
- Evolution of a genome-encoded bias in amino acid biosynthetic pathways is a potential indicator of amino acid dynamics in the environment.Molecular biology and evolution · 2014Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
backgroundThe COG database is the most popular collection of orthologous proteins from many different completely sequenced microbial genomes. Per definition, a cluster of orthologous groups (COG) within this database exclusively contains proteins that most likely achieve the same cellular function. Recently, the COG database was extended by assigning to every protein both the corresponding amino acid and its encoding nucleotide sequence resulting in the NUCOCOG database. This extended version of the COG database is a valuable resource connecting sequence features with the functionality of the respective proteins.
resultsHere we present ANCAC, a web tool and MySQL database for the analysis of amino acid, nucleotide, and codon frequencies in COGs on the basis of freely definable phylogenetic patterns. We demonstrate the usefulness of ANCAC by analyzing amino acid frequencies, codon usage, and GC-content in a species- or function-specific context. With respect to amino acids we, at least in part, confirm the cognate bias hypothesis by using ANCAC's NUCOCOG dataset as the largest one available for that purpose thus far.
conclusionsUsing the NUCOCOG datasets, ANCAC connects taxonomic, amino acid, and nucleotide sequence information with the functional classification via COGs and provides a GUI for flexible mining for sequence-bias. Thereby, to our knowledge, it is the only tool for the analysis of sequence composition in the light of physiological roles and phylogenetic context without requirement of substantial programming-skills.
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