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Neural Networks Predict Protein Structure and Function

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Artificial Neural Networks

Part of the book series: Methods in Molecular Biology™ ((MIMB,volume 458))

Abstract

Both supervised and unsupervised neural networks have been applied to the prediction of protein structure and function. Here, we focus on feedforward neural networks and describe how these learning machines can be applied to protein prediction. We discuss how to select an appropriate data set, how to choose and encode protein features into the neural network input, and how to assess the predictor's performance.

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Abbreviations

aa:

amino acids

AUC:

area under the ROC curve

FN:

false negative

FP:

false positive

FPR:

false- positive rate

NFP:

number of free parameters

NHN:

number of hidden nodes

NN:

feedforward neural network

PDB:

protein data bank

ROC:

receiver operating characteristics

SS:

secondary structure

TN:

true negative

TP:

true positive

TPR:

true-positive rate

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Acknowledgements

Thanks to Hans-Erik G. Aronson (Columbia) for computer assistance; thanks to Dariusz Przybylski (Columbia) for important discussions and very useful comments on the manuscript. This work was supported by Grants U54-GM072980 and U54 GM75026-01 from the National Institutes of Health (NIH) and Grant NIH/NLM R01-LM07329-01 from the NIH and the National Library of Medicine..

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Authors and Affiliations

  1. Department of Biochemistry and Molecular Biophysics, Columbia University, 1130 St. Nicholas Ave., NY 10032, New York, USA

    Marco Punta PhD

  2. Department of Biochemistry and Molecular Biophysics, Columbia University, Columbia University Center for Computational Biology and Bioinformatics; and North East Structural Genomics Consortium (NESG), Columbia University, New York, NY, USA

    Burkhard Rost PhD

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  1. Marco Punta PhD
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  2. Burkhard Rost PhD
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Correspondence to Marco Punta PhD .

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Editors and Affiliations

  1. ChemQuest, Sandown, Isle of Wight, United Kingdom, PO36 8LZ, UK

    David J. Livingstone

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© 2008 Humana Press, a part of Springer Science + Business Media, LLC

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Punta, M., Rost, B. (2008). Neural Networks Predict Protein Structure and Function. In: Livingstone, D.J. (eds) Artificial Neural Networks. Methods in Molecular Biology™, vol 458. Humana Press. https://doi.org/10.1007/978-1-60327-101-1_11

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  • DOI: https://doi.org/10.1007/978-1-60327-101-1_11

  • Publisher Name: Humana Press

  • Print ISBN: 978-1-58829-718-1

  • Online ISBN: 978-1-60327-101-1

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