Efficient computational model for classification of protein localization images using Extended Threshold Adjacency Statistics and Support Vector Machines.

Journal: Computer methods and programs in biomedicine
Published Date: Feb 2, 2018

Abstract

BACKGROUND AND OBJECTIVE: Discriminative and informative feature extraction is the core requirement for accurate and efficient classification of protein subcellular localization images so that drug development could be more effective. The objective of this paper is to propose a novel modification in the Threshold Adjacency Statistics technique and enhance its discriminative power.

Authors

  • Muhammad Tahir
    Department of Computer Science, Abdul Wali Khan University, Mardan, Pakistan.
  • Bismillah Jan
    Department of Computer and Information Sciences, Pakistan Institute of Engineering and Applied Sciences, Islamabad, Pakistan; Department of Computer Science, National University of Computer and Emerging Sciences, Peshawar Campus, Pakistan.
  • Maqsood Hayat
    Department of Computer Science, Abdul Wali Khan University Mardan, Mardan, KP, Pakistan. Electronic address: m.hayat@awkum.edu.pk.
  • Shakir Ullah Shah
    Department of Computer Science, National University of Computer and Emerging Sciences, Peshawar Campus, Pakistan.
  • Muhammad Amin
    Department of Computer Science, National University of Computer and Emerging Sciences, Peshawar Campus, Pakistan.

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