Computational study demonstrates genome-based species delimitation with confidence intervals in microorganisms, highlighting a path toward standardized digital taxonomy.
Despite the high accuracy of GBDP-based DDH prediction, inferences from limited empirical data are always associated with a certain degree of uncertainty. It is thus crucial to enrich in-silico DDH replacements with confidence-interval estimation, enabling the user to statistically evaluate the outcomes. Such methodological advancements, easily accessible through the web service at http://ggdc.dsmz.de, are crucial steps towards a consistent and truly genome sequence-based classification of microorganisms.
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Meier‐Kolthoff et al. (2013) studied this question.
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