This release introduces multiple performance optimizations which yield 2x to 5x speedup for most typical analyses and datasets. IMPORTANT: Due to change in defaults, the results are not compatible with previous raxml-ng versions. If you need to reproduce the behavior of raxml-ng 1.1.0 , add --extra compat-v11. Most changes can be also disabled one-by-one, please see instructions below: New defaults & optimizations --search1: use parsimony starting tree by default bootstrap: use parsimony starting trees by default (add --extra bs-start-rand to use random starting trees as before) faster CLV updates in SPR rounds by @togkousa (#157), add --extra fastclv-off to disable new logLH epsilon defaults by @tschuelia: eps=1000 for brlen triplet optim...
Motivation: Phylogenies are increasingly used in all fields of medical and biological research. More...
Despite recent advances achieved by application of high-performance computing methods and novel algo...
Phylogenetic tree reconstruction is one of the grand challenge problems in Bioinformatics. The searc...
Optimizations and extensions support model parameters in PAML format (--model PROTGTR{paml.txt}+G4)...
IMPORTANT: New defaults 20 starting trees = 10 random + 10 parsimony (was: 1 random) scaled/proport...
This release fixes several bugs found in v0.1.0 and adds following new features: most model paramet...
New features support for binary (aka presence/absence) and multistate (aka morphological) models c...
New features new support measure: Transfer Bootstrap Expectation (Lemoine et al., Nature 2018) : us...
New features/enhancements: new PHYLIP parser (much faster, supports interleaved format) ascertainme...
This is the first RAxML-NG release without "BETA" tag, which means we now consider it stable enough ...
CRITICAL BUGFIX: bootstrap support values were consistently underestimated if and only if --all com...
Enhancements: better input validation and error reporting (alignment/starting tree) Bugfixes: com...
Summary: RAxML-VI-HPC (randomized axelerated maximum likelihood for high performance computing) is a...
Motivation: Phylogenies are increasingly used in all fields of medical and biological research. M...
Abstract. Inference of phylogenetic trees comprising hundreds or even thousands of organisms based o...
Motivation: Phylogenies are increasingly used in all fields of medical and biological research. More...
Despite recent advances achieved by application of high-performance computing methods and novel algo...
Phylogenetic tree reconstruction is one of the grand challenge problems in Bioinformatics. The searc...
Optimizations and extensions support model parameters in PAML format (--model PROTGTR{paml.txt}+G4)...
IMPORTANT: New defaults 20 starting trees = 10 random + 10 parsimony (was: 1 random) scaled/proport...
This release fixes several bugs found in v0.1.0 and adds following new features: most model paramet...
New features support for binary (aka presence/absence) and multistate (aka morphological) models c...
New features new support measure: Transfer Bootstrap Expectation (Lemoine et al., Nature 2018) : us...
New features/enhancements: new PHYLIP parser (much faster, supports interleaved format) ascertainme...
This is the first RAxML-NG release without "BETA" tag, which means we now consider it stable enough ...
CRITICAL BUGFIX: bootstrap support values were consistently underestimated if and only if --all com...
Enhancements: better input validation and error reporting (alignment/starting tree) Bugfixes: com...
Summary: RAxML-VI-HPC (randomized axelerated maximum likelihood for high performance computing) is a...
Motivation: Phylogenies are increasingly used in all fields of medical and biological research. M...
Abstract. Inference of phylogenetic trees comprising hundreds or even thousands of organisms based o...
Motivation: Phylogenies are increasingly used in all fields of medical and biological research. More...
Despite recent advances achieved by application of high-performance computing methods and novel algo...
Phylogenetic tree reconstruction is one of the grand challenge problems in Bioinformatics. The searc...