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An Argumentation Theory-Based Multiagent Model to Annotate Proteins

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Advances in Bioinformatics and Computational Biology (BSB 2018)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 11228))

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Abstract

Many computational and experimental methods have been proposed for predicting functions performed by proteins. In silico methods are time and resource-consuming, due to the large amount of data used for annotation. Moreover, computational predictions for protein functions are usually incomplete and biased. Although some tools combine different annotation strategies to predict functions, biologists (human experts) have to use their knowledge to analyze and improve these predictions. This complex scenario presents suitable features for a multiagent approach, e.g., expert knowledge, distributed resources, and an environment that includes different computational methods. Also, argumentation theory can increase the expressiveness of biological knowledge of proteins, considering inconsistencies and incompleteness of information. The main goal of this work is to present an argumentation theory-based multiagent model to annotate proteins, called ArgMAS-AP. Additionally, we discuss a theoretical example with real data to evaluate the suitability of our model.

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Notes

  1. 1.

    Inconsistent is a protein that has at least one incorrectly assigned annotation.

  2. 2.

    https://www.uniprot.org/help/api.

  3. 3.

    http://www.uniprot.org/uniprot/P0ACC1.

  4. 4.

    http://www.uniprot.org/uniprot/Q6F0I4.

  5. 5.

    http://www.uniprot.org/uniprot/Q92G13.

  6. 6.

    https://bitbucket.org/erickok/baidd.

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Acknowledgments

D. Souza and W. Silva kindly thank CAPES for the scholarship. M. E. Walter thanks CNPq for the productivity fellowship (project 308524/2015-2). C. Ralha also thanks CNPq for the productivity fellowship (project 303863/2015-3).

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Authors and Affiliations

  1. University of Brasília, Brasília, Brazil

    Daniel S. Souza, Waldeyr M. C. Silva, Célia G. Ralha & Maria Emília M. T. Walter

  2. Federal Institute of Goiás, Formosa, Goiás, Brazil

    Waldeyr M. C. Silva

Authors
  1. Daniel S. Souza
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  2. Waldeyr M. C. Silva
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  3. Célia G. Ralha
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  4. Maria Emília M. T. Walter
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Corresponding author

Correspondence to Daniel S. Souza .

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Editors and Affiliations

  1. Instituto Tecnológico Vale, Belém, Brazil

    Ronnie Alves

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Souza, D.S., Silva, W.M.C., Ralha, C.G., Walter, M.E.M.T. (2018). An Argumentation Theory-Based Multiagent Model to Annotate Proteins. In: Alves, R. (eds) Advances in Bioinformatics and Computational Biology. BSB 2018. Lecture Notes in Computer Science(), vol 11228. Springer, Cham. https://doi.org/10.1007/978-3-030-01722-4_7

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  • DOI: https://doi.org/10.1007/978-3-030-01722-4_7

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