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Systematic Biology is a peer-reviewed journal published by Oxford University Press, covering Genetic diversity and population structure, Genomics and Phylogenetic Studies, Evolution and Paleontology Studies. Over its lifetime it has published 5,032 papers, which have received 488,620 citations.
| Publisher | Oxford University Press |
|---|---|
| Reference style | Author–year (OUP) Author–year — (Smith, 2023) in the text Smith, A., Jones, B. and Lee, C. (2023) 'A representative article title', Systematic Biology, 12(3), pp. 45–58.
Formats any DOI in the closest standard style — Systematic Biology has no published style definition, so this is an approximation. No sign-up. |
| Publishes research in | Genetic diversity and population structure Genomics and Phylogenetic Studies Evolution and Paleontology Studies Plant and animal studies Species Distribution and Climate Change |
| ISSN | 1063-5157 |
| Citation impact (2-yr) | 5.91 |
| h-index | 282 |
| i10-index | 2,964 |
| Article processing charge | $1,984 |
| Top institutions publishing here | American Museum of Natural History |
| Journal website | sysbio.oxfordjournals.org |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
Since its introduction in 2001, MrBayes has grown in popularity as a software package for Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) methods. With this note, we announce the release of version 3.2, a major upgrade to the latest official release presented in 2003. The new version provides convergence diagnostics and allows multiple…
PhyML is a phylogeny software based on the maximum-likelihood principle. Early PhyML versions used a fast algorithm performing nearest neighbor interchanges to improve a reasonable starting tree topology. Since the original publication (Guindon S., Gascuel O. 2003. A simple, fast and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst. Biol. 52:696-704), PhyML has…
The increase in the number of large data sets and the complexity of current probabilistic sequence evolution models necessitates fast and reliable phylogeny reconstruction methods. We describe a new approach, based on the maximum- likelihood principle, which clearly satisfies these requirements. The core of this method is a simple hill-climbing algorithm that adjusts tree topology…
Bayesian inference of phylogeny using Markov chain Monte Carlo (MCMC) plays a central role in understanding evolutionary history from molecular sequence data. Visualizing and analyzing the MCMC-generated samples from the posterior distribution is a key step in any non-trivial Bayesian inference. We present the software package Tracer (version 1.7) for visualizing and analyzing the MCMC…
Despite recent advances achieved by application of high-performance computing methods and novel algorithmic techniques to maximum likelihood (ML)-based inference programs, the major computational bottleneck still consists in the computation of bootstrap support values. Conducting a probably insufficient number of 100 bootstrap (BS) analyses with current ML programs on large datasets-either with respect to the number…
