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Improved Disorder Prediction by Combination of Orthogonal Approaches

Author

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  • Avner Schlessinger
  • Marco Punta
  • Guy Yachdav
  • Laszlo Kajan
  • Burkhard Rost

Abstract

Disordered proteins are highly abundant in regulatory processes such as transcription and cell-signaling. Different methods have been developed to predict protein disorder often focusing on different types of disordered regions. Here, we present MD, a novel META-Disorder prediction method that molds various sources of information predominantly obtained from orthogonal prediction methods, to significantly improve in performance over its constituents. In sustained cross-validation, MD not only outperforms its origins, but it also compares favorably to other state-of-the-art prediction methods in a variety of tests that we applied. Availability: http://www.rostlab.org/services/md/

Suggested Citation

  • Avner Schlessinger & Marco Punta & Guy Yachdav & Laszlo Kajan & Burkhard Rost, 2009. "Improved Disorder Prediction by Combination of Orthogonal Approaches," PLOS ONE, Public Library of Science, vol. 4(2), pages 1-10, February.
  • Handle: RePEc:plo:pone00:0004433
    DOI: 10.1371/journal.pone.0004433
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    References listed on IDEAS

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    1. Jenny Gu & Michael Gribskov & Philip E Bourne, 2006. "Wiggle—Predicting Functionally Flexible Regions from Primary Sequence," PLOS Computational Biology, Public Library of Science, vol. 2(7), pages 1-17, July.
    2. Kenji Sugase & H. Jane Dyson & Peter E. Wright, 2007. "Mechanism of coupled folding and binding of an intrinsically disordered protein," Nature, Nature, vol. 447(7147), pages 1021-1025, June.
    3. Avner Schlessinger & Jinfeng Liu & Burkhard Rost, 2007. "Natively Unstructured Loops Differ from Other Loops," PLOS Computational Biology, Public Library of Science, vol. 3(7), pages 1-12, July.
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    1. Esmeralda Vicedo & Avner Schlessinger & Burkhard Rost, 2015. "Environmental Pressure May Change the Composition Protein Disorder in Prokaryotes," PLOS ONE, Public Library of Science, vol. 10(8), pages 1-21, August.
    2. Jiangning Song & Hao Tan & Mingjun Wang & Geoffrey I Webb & Tatsuya Akutsu, 2012. "TANGLE: Two-Level Support Vector Regression Approach for Protein Backbone Torsion Angle Prediction from Primary Sequences," PLOS ONE, Public Library of Science, vol. 7(2), pages 1-16, February.
    3. Zhiheng Wang & Qianqian Yang & Tonghua Li & Peisheng Cong, 2015. "DisoMCS: Accurately Predicting Protein Intrinsically Disordered Regions Using a Multi-Class Conservative Score Approach," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-16, June.

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