Molecular Clock Calibrations and Metazoan Divergence Dates
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Summary
Recalibration of the protein data using these fossil dates indicates that metazoans diverged between 791 and 528 million years ago, a result broadly consistent with the palaeontological documentation of the ``Cambrian explosion.
- Type
- article
- Published
- 1999-01-01
- Cited by
- 156
- References
- 48
- OpenAlex
- https://openalex.org/W10473780
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:1629316
Keywords
Derecho, Philosophy, Humanities
References
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- Caveats on the Use of Fossil Calibrations for Molecular Dating: A Comment on Near et al.
- Evaluating fossil calibrations for dating phylogenies in light of rates of molecular evolution: a comparison of three approaches.
- Biologie moléculaire et phylogenèse des Lémuriformes (Primates de Madagascar)
- Environmentally Influenced Duplication Patterns Followed by Functional Shifts Fueling the Evolution of Metazoan Sensory Systems
- Computational approaches to discovering differentiation genes in the peripheral nervous system of Drosophila melanogaster
- Molecular systematics of the leafy liverwort family Lophoziaceae cavers
- Bayesian molecular phylogenetics : estimation of divergence dates and hypothesis testing
- Phylogenetic Supertrees
- Accounting for calibration uncertainty in phylogenetic estimation of evolutionary divergence times.
- The neomuran origin of archaebacteria, the negibacterial root of the universal tree and bacterial megaclassification.
- Older than New Caledonia emergence? A molecular phylogenetic study of the eneopterine crickets (Orthoptera: Grylloidea)
- Potassium- or sodium-efflux ATPase, a key enzyme in the evolution of fungi.
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- Sourcing the Code: Searching for the Evolutionary Origins of Cannabinoid Receptors, Vanilloid Receptors, and Anandamide
- Constraints on the timescale of animal evolutionary history
- Molecular Clock and Gene Function
- Phylochronology of early metazoans: combined evidence from molecular and fossil data
- Dating the arthropod tree based on large-scale transcriptome data.
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