IDEAS home Printed from https://ideas.repec.org/a/adp/jbboaj/v7y2018i3p54-55.html
   My bibliography  Save this article

Approximate Bayesian Computation for Biological Science

Author

Listed:
  • Ritabrata Dutta

    (Institute of Computational Science, Universita della Svizzera italiana, Switzerland)

  • Antonietta Mira

    (Department of Science and High Technology, Universita degli Studi degli Insubria, Italy)

Abstract

Approximate Bayesian computation (ABC) provides us a rigorous tool to perform parameter inference for models without an easily accessible likelihood function. Here we give a short introduction to ABC, focusing on applications in biological science. Furthermore, we introduce users to a Python suite implementing ABC algorithms, with optimal use of high performance computing facilities.

Suggested Citation

  • Ritabrata Dutta & Antonietta Mira, 2018. "Approximate Bayesian Computation for Biological Science," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 7(3), pages 54-55, July.
    • Handle: RePEc:adp:jbboaj:v:7:y:2018:i:3:p:54-55
    DOI: 10.19080/BBOAJ.2018.07.555715
    as

    Download full text from publisher

    File URL: https://juniperpublishers.com/bboaj/pdf/BBOAJ.MS.ID.555715.pdf
    Download Restriction: no
    File URL: https://juniperpublishers.com/bboaj/BBOAJ.MS.ID.555715.php
    Download Restriction: no
    File URL: https://libkey.io/10.19080/BBOAJ.2018.07.555715?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Esteban A. Martinez & Christine A. Muschik & Philipp Schindler & Daniel Nigg & Alexander Erhard & Markus Heyl & Philipp Hauke & Marcello Dalmonte & Thomas Monz & Peter Zoller & Rainer Blatt, 2016. "Real-time dynamics of lattice gauge theories with a few-qubit quantum computer," Nature, Nature, vol. 534(7608), pages 516-519, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Stefan Birnkammer & Alvise Bastianello & Michael Knap, 2022. "Prethermalization in one-dimensional quantum many-body systems with confinement," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    2. Yasar Y. Atas & Jinglei Zhang & Randy Lewis & Amin Jahanpour & Jan F. Haase & Christine A. Muschik, 2021. "SU(2) hadrons on a quantum computer via a variational approach," Nature Communications, Nature, vol. 12(1), pages 1-11, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:adp:jbboaj:v:7:y:2018:i:3:p:54-55. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Robert Thomas (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.