A lightweight classification of adaptor proteins using transformer networks.

Journal: BMC bioinformatics
PMID: 36333658

Abstract

BACKGROUND: Adaptor proteins play a key role in intercellular signal transduction, and dysfunctional adaptor proteins result in diseases. Understanding its structure is the first step to tackling the associated conditions, spurring ongoing interest in research into adaptor proteins with bioinformatics and computational biology. Our study aims to introduce a small, new, and superior model for protein classification, pushing the boundaries with new machine learning algorithms.

Authors

  • Sylwan Rahardja
    School of Computing, University of Eastern Finland, Joensuu, Finland.
  • Mou Wang
    School of Marine Science and Technology, Northwestern Polytechnical University, 710072, Xi'an, China.
  • Binh P Nguyen
    School of Mathematics and Statistics, Victoria University of Wellington, Kelburn Parade, Wellington 6140, New Zealand.
  • Pasi Fränti
    School of Computing, University of Eastern Finland, Joensuu, Finland.
  • Susanto Rahardja
    School of Marine Science and Technology, Northwestern Polytechnical University, 127 West Youyi Road, Xi'an, 710072, China. susantorahardja@ieee.org.

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