IDEAS home Printed from https://ideas.repec.org/a/plo/pcbi00/1004777.html
   My bibliography  Save this article

The Maximum Entropy Fallacy Redux?

Author

Listed:
  • Erik Aurell

Abstract

No abstract is available for this item.

Suggested Citation

  • Erik Aurell, 2016. "The Maximum Entropy Fallacy Redux?," PLOS Computational Biology, Public Library of Science, vol. 12(5), pages 1-7, May.
    • Handle: RePEc:plo:pcbi00:1004777
    DOI: 10.1371/journal.pcbi.1004777
    as

    Download full text from publisher

    File URL: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004777
    Download Restriction: no
    File URL: https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1004777&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pcbi.1004777?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. Christoph Feinauer & Marcin J Skwark & Andrea Pagnani & Erik Aurell, 2014. "Improving Contact Prediction along Three Dimensions," PLOS Computational Biology, Public Library of Science, vol. 10(10), pages 1-13, October.
    2. Erik van Nimwegen, 2016. "Inferring Contacting Residues within and between Proteins: What Do the Probabilities Mean?," PLOS Computational Biology, Public Library of Science, vol. 12(5), pages 1-10, May.
    3. Marcin J Skwark & Daniele Raimondi & Mirco Michel & Arne Elofsson, 2014. "Improved Contact Predictions Using the Recognition of Protein Like Contact Patterns," PLOS Computational Biology, Public Library of Science, vol. 10(11), pages 1-14, November.
    4. Richard R Stein & Debora S Marks & Chris Sander, 2015. "Inferring Pairwise Interactions from Biological Data Using Maximum-Entropy Probability Models," PLOS Computational Biology, Public Library of Science, vol. 11(7), pages 1-22, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Pedro L Teixeira & Jeff L Mendenhall & Sten Heinze & Brian Weiner & Marcin J Skwark & Jens Meiler, 2017. "Membrane protein contact and structure prediction using co-evolution in conjunction with machine learning," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-24, May.
    2. Erik van Nimwegen, 2016. "Inferring Contacting Residues within and between Proteins: What Do the Probabilities Mean?," PLOS Computational Biology, Public Library of Science, vol. 12(5), pages 1-10, May.

    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. Pedro L Teixeira & Jeff L Mendenhall & Sten Heinze & Brian Weiner & Marcin J Skwark & Jens Meiler, 2017. "Membrane protein contact and structure prediction using co-evolution in conjunction with machine learning," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-24, May.
    2. Andrew F Neuwald & Stephen F Altschul, 2016. "Inference of Functionally-Relevant N-acetyltransferase Residues Based on Statistical Correlations," PLOS Computational Biology, Public Library of Science, vol. 12(12), pages 1-30, December.
    3. Erik van Nimwegen, 2016. "Inferring Contacting Residues within and between Proteins: What Do the Probabilities Mean?," PLOS Computational Biology, Public Library of Science, vol. 12(5), pages 1-10, May.
    4. Md Tauhidul Islam & Lei Xing, 2023. "Cartography of Genomic Interactions Enables Deep Analysis of Single-Cell Expression Data," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    5. Sheng Wang & Siqi Sun & Zhen Li & Renyu Zhang & Jinbo Xu, 2017. "Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model," PLOS Computational Biology, Public Library of Science, vol. 13(1), pages 1-34, January.
    6. Tatjana Braun & Julia Koehler Leman & Oliver F Lange, 2015. "Combining Evolutionary Information and an Iterative Sampling Strategy for Accurate Protein Structure Prediction," PLOS Computational Biology, Public Library of Science, vol. 11(12), pages 1-20, December.
    7. Sophia S Liu & Adam J Hockenberry & Andrea Lancichinetti & Michael C Jewett & Luís A N Amaral, 2016. "NullSeq: A Tool for Generating Random Coding Sequences with Desired Amino Acid and GC Contents," PLOS Computational Biology, Public Library of Science, vol. 12(11), pages 1-12, November.
    8. Elena Facco & Andrea Pagnani & Elena Tea Russo & Alessandro Laio, 2019. "The intrinsic dimension of protein sequence evolution," PLOS Computational Biology, Public Library of Science, vol. 15(4), pages 1-16, April.
    9. Lorenzo Asti & Guido Uguzzoni & Paolo Marcatili & Andrea Pagnani, 2016. "Maximum-Entropy Models of Sequenced Immune Repertoires Predict Antigen-Antibody Affinity," PLOS Computational Biology, Public Library of Science, vol. 12(4), pages 1-20, April.
    10. Rajita Menon & Vivek Ramanan & Kirill S Korolev, 2018. "Interactions between species introduce spurious associations in microbiome studies," PLOS Computational Biology, Public Library of Science, vol. 14(1), pages 1-20, January.

    More about this item

    Statistics

    Access and download statistics

    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:plo:pcbi00:1004777. 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: ploscompbiol (email available below). General contact details of provider: https://journals.plos.org/ploscompbiol/ .

    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.