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Identification and Correction of Erroneous Protein Sequences in Public Databases

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Data Mining Techniques for the Life Sciences

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1415))

Abstract

Correct prediction of the structure of protein-coding genes of higher eukaryotes is a difficult task therefore public sequence databases incorporating predicted sequences are increasingly contaminated with erroneous sequences. The high rate of misprediction has serious consequences since it significantly affects the conclusions that may be drawn from genome-scale sequence analyses.

Here we describe the MisPred and FixPred approaches that may help the identification and correction of erroneous sequences. The rationale of these approaches is that a protein sequence is likely to be erroneous if some of its features conflict with our current knowledge about proteins.

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Acknowledgement

This work was supported by grants from the National Office for Research and Technology of Hungary (TECH_09_A1-FixPred9) and the Hungarian Scientific Research Fund (OTKA 101201).

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Authors and Affiliations

  1. Institute of Enzymology, Research Centre for Natural Sciences, Hungarian Academy of Sciences, 286, Budapest, H-1519, Hungary

    László Patthy

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  1. László Patthy
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Correspondence to László Patthy .

Editor information

Editors and Affiliations

  1. Max F. Perutz Laboratories GmbH, Universität Wien, Wien, Austria

    Oliviero Carugo

  2. Technology and Research (A*STAR), Agency for Science, Singapore, Singapore

    Frank Eisenhaber

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Patthy, L. (2016). Identification and Correction of Erroneous Protein Sequences in Public Databases. In: Carugo, O., Eisenhaber, F. (eds) Data Mining Techniques for the Life Sciences. Methods in Molecular Biology, vol 1415. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-3572-7_9

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  • DOI: https://doi.org/10.1007/978-1-4939-3572-7_9

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-3570-3

  • Online ISBN: 978-1-4939-3572-7

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