Gene selection and classification in microarray datasets using a hybrid approach of PCC-BPSO/GA with multi classifiers

Shilan S. Hameed, Fahmi F. Muhammad, Rohayanti Hassan, Faisal Saeed*

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    25 Citations (SciVal)
    Original languageEnglish
    Pages (from-to)868-880
    Number of pages13
    JournalJournal of Computer Science
    Volume14
    Issue number6
    DOIs
    Publication statusPublished (VoR) - 2018

    Funding

    The authors are thankful to the Ministry of Higher Education (MOHE) and the Research Management Centre (RMC) at the Universiti Teknologi Malaysia (UTM) for their support under the Research University Grant Category (VOT Q.J130000.2528.16H74).

    FundersFunder number
    Research Management Centre
    Ministry of Higher Education
    Universiti Teknologi MalaysiaVOT Q.J130000.2528.16H74

      Keywords

      • BPSO
      • GA
      • Hybrid
      • Microarray
      • Pearson's Correlation Coefficient

      Fingerprint

      Dive into the research topics of 'Gene selection and classification in microarray datasets using a hybrid approach of PCC-BPSO/GA with multi classifiers'. Together they form a unique fingerprint.

      Cite this