The Experts below are selected from a list of 6651 Experts worldwide ranked by ideXlab platform

Evan Sinukoff - One of the best experts on this subject based on the ideXlab platform.

  • radvel the radial velocity modeling toolkit
    Publications of the Astronomical Society of the Pacific, 2018
    Co-Authors: Benjamin J Fulton, Erik A Petigura, Sarah Blunt, Evan Sinukoff
    Abstract:

    RadVel is an open-source Python package for modeling Keplerian orbits in radial velocity (RV) timeseries. RadVel provides a convenient framework to fit RVs using maximum a posteriori optimization and to compute robust confidence intervals by sampling the posterior probability density via Markov Chain Monte Carlo (MCMC). RadVel allows users to float or fix parameters, impose priors, and perform Bayesian model comparison. We have implemented real-time MCMC convergence tests to ensure adequate sampling of the posterior. RadVel can output a number of publication-quality plots and tables. Users may Interface with RadVel through a convenient Command-Line Interface or directly from Python. The code is object-oriented and thus naturally extensible. We encourage contributions from the community. Documentation is available at http://radvel.readthedocs.io.

  • radvel the radial velocity modeling toolkit
    arXiv: Instrumentation and Methods for Astrophysics, 2018
    Co-Authors: Benjamin J Fulton, Erik A Petigura, Sarah Blunt, Evan Sinukoff
    Abstract:

    RadVel is an open source Python package for modeling Keplerian orbits in radial velocity (RV) time series. RadVel provides a convenient framework to fit RVs using maximum a posteriori optimization and to compute robust confidence intervals by sampling the posterior probability density via Markov Chain Monte Carlo (MCMC). RadVel allows users to float or fix parameters, impose priors, and perform Bayesian model comparison. We have implemented realtime MCMC convergence tests to ensure adequate sampling of the posterior. RadVel can output a number of publication-quality plots and tables. Users may Interface with RadVel through a convenient Command-Line Interface or directly from Python. The code is object-oriented and thus naturally extensible. We encourage contributions from the community. Documentation is available at this http URL

Jacob D. Durrant - One of the best experts on this subject based on the ideXlab platform.

  • webina an open source library and web app that runs autodock vina entirely in the web browser
    Bioinformatics, 2020
    Co-Authors: Yuri Kochnev, Erich Hellemann, Kevin C. Cassidy, Jacob D. Durrant
    Abstract:

    MOTIVATION Molecular docking is a computational technique for predicting how a small molecule might bind a macromolecular target. Among docking programs, AutoDock Vina is particularly popular. Like many docking programs, Vina requires users to download/install an executable file and to run that file from a Command-Line Interface. Choosing proper configuration parameters and analyzing Vina output is also sometimes challenging. These issues are particularly problematic for students and novice researchers. RESULTS We created Webina, a new version of Vina, to address these challenges. Webina runs Vina entirely in a web browser, so users need only visit a Webina-enabled webpage. The docking calculations take place on the user's own computer rather than a remote server. AVAILABILITY AND IMPLEMENTATION A working version of the open-source Webina app can be accessed free of charge from http://durrantlab.com/webina. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics onLine.

  • Webina: An Open-Source Library and Web App that Runs AutoDock Vina Entirely in the Web Browser.
    Bioinformatics, 2020
    Co-Authors: Yuri Kochnev, Erich Hellemann, Kevin C. Cassidy, Jacob D. Durrant
    Abstract:

    MOTIVATION Molecular docking is a computational technique for predicting how a small molecule might bind a macromolecular target. Among docking programs, AutoDock Vina is particularly popular. Like many docking programs, Vina requires users to download/install an executable file and to run that file from a Command-Line Interface. Choosing proper configuration parameters and analyzing Vina output is also sometimes challenging. These issues are particularly problematic for students and novice researchers. RESULTS We created Webina, a new version of Vina, to address these challenges. Webina runs Vina entirely in a web browser, so users need only visit a Webina-enabled webpage. The docking calculations take place on the user's own computer rather than a remote server. AVAILABILITY A working version of the open-source Webina app can be accessed free of charge from http://durrantlab.com/webina. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics onLine.

Benjamin J Fulton - One of the best experts on this subject based on the ideXlab platform.

  • radvel the radial velocity modeling toolkit
    Publications of the Astronomical Society of the Pacific, 2018
    Co-Authors: Benjamin J Fulton, Erik A Petigura, Sarah Blunt, Evan Sinukoff
    Abstract:

    RadVel is an open-source Python package for modeling Keplerian orbits in radial velocity (RV) timeseries. RadVel provides a convenient framework to fit RVs using maximum a posteriori optimization and to compute robust confidence intervals by sampling the posterior probability density via Markov Chain Monte Carlo (MCMC). RadVel allows users to float or fix parameters, impose priors, and perform Bayesian model comparison. We have implemented real-time MCMC convergence tests to ensure adequate sampling of the posterior. RadVel can output a number of publication-quality plots and tables. Users may Interface with RadVel through a convenient Command-Line Interface or directly from Python. The code is object-oriented and thus naturally extensible. We encourage contributions from the community. Documentation is available at http://radvel.readthedocs.io.

  • radvel the radial velocity modeling toolkit
    arXiv: Instrumentation and Methods for Astrophysics, 2018
    Co-Authors: Benjamin J Fulton, Erik A Petigura, Sarah Blunt, Evan Sinukoff
    Abstract:

    RadVel is an open source Python package for modeling Keplerian orbits in radial velocity (RV) time series. RadVel provides a convenient framework to fit RVs using maximum a posteriori optimization and to compute robust confidence intervals by sampling the posterior probability density via Markov Chain Monte Carlo (MCMC). RadVel allows users to float or fix parameters, impose priors, and perform Bayesian model comparison. We have implemented realtime MCMC convergence tests to ensure adequate sampling of the posterior. RadVel can output a number of publication-quality plots and tables. Users may Interface with RadVel through a convenient Command-Line Interface or directly from Python. The code is object-oriented and thus naturally extensible. We encourage contributions from the community. Documentation is available at this http URL

Matthew Scotch - One of the best experts on this subject based on the ideXlab platform.

  • pyjacqq python implementation of jacquez s q statistics for space time clustering of disease exposure in case control studies
    Journal of Statistical Software, 2016
    Co-Authors: Saman Jirjies, Garrick Wallstrom, Rolf U Halden, Matthew Scotch
    Abstract:

    Jacquez's Q is a set of statistics for detecting the presence and location of space-time clusters of disease exposure. Until now, the only implementation was available in the proprietary SpaceStat software which is not suitable for a pipeLine Linux environment. We have developed an open source implementation of Jacquez's Q statistics in Python using an object-oriented approach. The most recent source code for the implementation is available at https://github.com/sjirjies/pyJacqQ under the GPL-3. It has a Command Line Interface and a Python application programming Interface.

Liao Haining - One of the best experts on this subject based on the ideXlab platform.