Software - D. Silvestro group

We develop open source programs, mostly in Python and R, implementing Bayesian algorithms and machine learning methods with applications in evolutionary (paleo)biology.

  • Diversification and extinction models

    ADE-NN

    Estimation of age-dependent extinction using Deep Neural Networks (written in Python).

    Available on GitHub

     

    BAYESRATE

    Bayesian estimation of diversification rates from dated phylogenies (Python and R).

    Available on GitHub

     

    LITERATE

    Python program to estimate origination and extinction from cultural and technological data.

    Available on GitHub 

     

    MCMCDIVERSITREE

    Bayesian implementation of trait-dependent birth-death models to estimate speciation and extinction rates from phylogenetic trees.

    Available on GitHub 

     

    PYRATE

    Bayesian estimation of speciation, extinction, dispersal, and preservation rates from fossil occurrence data.

    Available on GitHub 

     

  • Phylogenetics and trait evolution

    RAXMLGUI

    A graphical front-end for RAxML.

    Available on GitHub 

     

    FOSSILBM

    Bayesian estimation of trait evolution under a fossilized Brownian motion model of evolution (written in R).

    Available on GitHub 

     

    BITE

    Bayesian Integrative models for Trait Evolution (written in R).

    Available on GitHub 

     

    COEVRJ

    Joint Bayesian estimation of molecular coevolution and phylogenetic trees.

    Available on Bitbucket 

  • Biogeography and spatial data

    COORDINATECLEANER

    R package to clean geographic occurrence data.

    Available on CRAN 

     

    PROVENANCEFINDER

    Likelihood estimation of sediment provenance based on radiometric date matching (R).

    Available on GitHub 

     

    SAMPBIAS

    R package to evaluate geographic sampling biases in species distribution data.

    Available on GitHub