Statistical characterization and classification of colon microarray gene expression data using multiple machine learning paradigms.

Journal: Computer methods and programs in biomedicine
PMID: 31200905

Abstract

OBJECTIVE: A colon microarray data is a repository of thousands of gene expressions with different strengths for each cancer cell. It is necessary to detect which genes are responsible for cancer growth. This study presents an exhaustive comparative study of different machine learning (ML) systems which serves two major purposes: (a) identification of high risk differential genes using statistical tests and (b) development of a ML strategy for predicting cancer genes.

Authors

  • Md Maniruzzaman
    Department of Statistics, University of Rajshahi, Rajshahi, Bangladesh. Electronic address: monir.stat91@gmail.com.
  • Md Jahanur Rahman
    Department of Statistics, University of Rajshahi, Rajshahi, Bangladesh.
  • Benojir Ahammed
    Statistics Discipline, Khulna University, Khulna, Bangladesh.
  • Md Menhazul Abedin
    Statistics Discipline, Khulna University, Khulna, Bangladesh.
  • Harman S Suri
    Brown University, Providence, RI, USA; Monitoring and Diagnostic Division, AtheroPoint™, Roseville, CA, USA.
  • Mainak Biswas
    Department of Computer Science and Engineering, NIT, Goa, India.
  • Ayman El-Baz
    Bioengineering Department, The University of Louisville, Louisville, KY, USA.
  • Petros Bangeas
    Department of Surgery, Papageorgiou Hospital, Aristotle University Thessaloniki, Greece.
  • Georgios Tsoulfas
    Department of Surgery, Aristotle University of Thessaloniki, Thessaloniki, Greece.
  • Jasjit S Suri
    Advanced Knowledge Engineering Center, Global Biomedical Technologies, Inc., Roseville, CA, USA. Electronic address: jsuri@comcast.net.

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