October 13, 2016BMC Bioinformatics60 citationsOpen Access

A scalability study of phylogenetic network inference methods using empirical datasets and simulations involving a single reticulation

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Abstract

We conclude that the state of the art of phylogenetic network inference lags well behind the scope of current phylogenomic studies. New algorithmic development is critically needed to address this methodological gap.

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Hejase et al. (2016) studied this question.

synapsesocial.com/papers/69dd12de7a14526fc01332de https://doi.org/10.1186/s12859-016-1277-1

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October 13, 2016BMC Bioinformatics60 citationsOpen Access

A scalability study of phylogenetic network inference methods using empirical datasets and simulations involving a single reticulation

HHHussein A. Hejase KLKevin J. Liu

Key Points

Key points are not available for this paper at this time.

Abstract

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Cite This Study

Hejase et al. (2016) studied this question.

synapsesocial.com/papers/69dd12de7a14526fc01332de https://doi.org/10.1186/s12859-016-1277-1

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