Author

F. Derakhshandeh

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Evolutionary Biology· 1

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Research Focus:benchmarking· 1 Approach:deep learning· 1 Assay:DNA methylation· 1 Research Focus:phylogenetics / evolution· 1 Approach:statistical model· 1

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C. Mayer· 1 shared N. Kulikov· 1 shared

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2023-2023 · peak 1/yr

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1 shared paperEvolutionary Biology

C. Mayer

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1 paper

Recent·Most cited

Machine learning can be as good as maximum likelihood when reconstructing phylogenetic trees and determining the best evolutionary model on four taxon alignments

N. Kulikov, F. Derakhshandeh, C. Mayer

This study shows neural networks can accurately predict evolutionary models and phylogenetic tree topologies for four-taxon alignments, often matching Maximum Likelihood performance while being faster.

bioRxiv · Jul 12, 2023Evolutionary Biology