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Subcellular Localization of Gram-Negative Proteins Using Label Powerset Encoding

  • Hasnaeen Ferdous
  • Raihan Uddin
  • Swakkhar ShatabdaEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 755)

Abstract

Bacterial proteins play an important role in cell biology due to their importance in drug design and antibiotics research. The localization of bacterial proteins is very important since the function of a protein is closely linked with its location. A single gram-negative bacteria proteins can be located in multiple locations in a protein. Prediction of subcellular locations of gram-negative bacteria proteins is thus more difficult. In this paper, we propose a novel method for subcellular localization of gram-negative bacteria. Our method uses label powerset encoding scheme for the associated multi-label classification problem. Using a set of effective features also used in the literature our encoding significantly improves over the traditional approaches on several base classifiers. Our method was tested using a standard benchmark dataset and showed promising results.

Keywords

Supervised learning Classification problem Label encoding Protein subcellular localization 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Hasnaeen Ferdous
    • 1
  • Raihan Uddin
    • 1
  • Swakkhar Shatabda
    • 1
    Email author
  1. 1.Department of Computer Science and EngineeringUnited International UniversityDhakaBangladesh

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