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Plant and Animal Sub Cellular Component Localization Prediction using Multiple Combination of various machine learning Approaches

Publication Type : Journal Article

Publisher : (2018) International Journal of Engineering and Technology(UAE)

Source : (2018) International Journal of Engineering and Technology(UAE), 7, pp. 221-224.

Url : https://www.scopus.com/inward/record.uri?eid=2-s2.0-85046266816&partnerID=40&md5=87c45ae167695e7212e84288d9b9fe

Campus : Mysuru

School : School of Arts and Sciences

Department : Computer Science

Year : 2018

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.

Cite this Research Publication : Bipin Nair, B.J., Ashik, P.V., Plant and Animal sub cellular component localization prediction using multiple combination of various
machine learning approaches, (2018) International Journal of Engineering and Technology(UAE), 7, pp. 221-224, 2018

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