What question did this study set out to answer?

Integrate confidence-interval estimation and enhanced distance functions into in-silico DNA-DNA hybridization (DDH) methods to improve statistical rigor in microbial species delimitation.

February 21, 2013BMC BioinformaticsOpen Access

Genome sequence-based species delimitation with confidence intervals and improved distance functions

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Integrate confidence-interval estimation and enhanced distance functions into in-silico DNA-DNA hybridization (DDH) methods to improve statistical rigor in microbial species delimitation.
Incorporated confidence-interval calculations into Genome BLAST Distance Phylogeny (GBDP)-based digital DDH models to measure uncertainty in empirical inferences.
Deployed the enhanced distance functions and statistical estimators into a publicly accessible online service (GGDC).
Provides measurable statistical uncertainty ranges alongside digital DDH predictions for microbial taxonomic identification.
Facilitates standardized, reproducible microbial genome classification through an open-access web implementation.

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Implication

Computational study demonstrates genome-based species delimitation with confidence intervals in microorganisms, highlighting a path toward standardized digital taxonomy.

Cite This Study

Meier‐Kolthoff et al. (2013) studied this question.

synapsesocial.com/papers/69d6f4da733a2b54c8aa8755 https://doi.org/10.1186/1471-2105-14-60

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Implication

Computational study demonstrates genome-based species delimitation with confidence intervals in microorganisms, highlighting a path toward standardized digital taxonomy.

Genome sequence-based species delimitation with confidence intervals and improved distance functions

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Discussion

Implication

Cite This Study

Genome sequence-based species delimitation with confidence intervals and improved distance functions

Key Points

Discussion

Implication

Cite This Study

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