Plant and Animal sub cellular component localization prediction using multiple combination of various machine learning approaches

  • Authors

    • Bipin Nair B J
    • Ashik P.v
    2018-03-01
    https://doi.org/10.14419/ijet.v7i1.9.9828
  • Amino Acid Composition (AAC), Sub Cellular Localization, Gene Ontology (GO

  • Abstract

    Membrane proteins are encoded in the genome and functionally important in the living organisms. Information on subcellular localization of cellular proteins has a significant role in the function of cell organelles. Discovery of drug target and system biology between localization and biological function are highly correlated. Therefore, we are predicting the localization of protein using various machine learning approaches. The prediction system based on the integration of the outcome of five sequence based sub-classifiers. The subcellular localization prediction of the final result is based on protein profile vector, which is a result of the sub-classifiers.

  • References

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  • How to Cite

    Nair B J, B., & P.v, A. (2018). Plant and Animal sub cellular component localization prediction using multiple combination of various machine learning approaches. International Journal of Engineering & Technology, 7(1.9), 221-224. https://doi.org/10.14419/ijet.v7i1.9.9828

    Received date: 2018-03-03

    Accepted date: 2018-03-03

    Published date: 2018-03-01