Motif Structure Prediction in Distributed Framework using Machine Learning Algorithms
D. Shine Babu1, Latha Parthiban2, Sivagama Sundari. G3

1D. Shine Babu, Research Scholar, Department of Computer Science and Engineering, Sathayabama Institute of Science and Technology, Chennai (Tamil Nadu), India.
2Dr. Latha Parthiban, Research Supervisor, Department of Computer Science, Pondicherry University CC, Puducherry, India.
3Sivagama Sundari. G, Associate Professor, M.V.Jayaraman College of Engineering, Bangalore (Karnataka), India.
Manuscript received on 12 February 2019 | Revised Manuscript received on 02 March 2019 | Manuscript Published on 08 June 2019 | PP: 70-74 | Volume-7 Issue-5S4, February 2019 | Retrieval Number: E10140275S419/19©BEIESP
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Abstract: It is a challenging work for researchers to design and develop new techniques for processing of data and development of new drugs. A distributed approach, which will work for huge amount of protein data and for predicting the motif structures in a large scale is proposed in this paper. ANNs has been used as classifier to estimate the motif structure of proteins. It will be helpful for the researchers and aids in understanding the relation between protein sequence and structure using which new drugs and novel enzymes can be designed after analyzing the protein structures.
Keywords: Bioinformatics, Big Data, Map Reduce, Machine Learning, Apache Hadoop, Protein Structure Prediction.
Scope of the Article: Patterns and Frameworks