Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/4599
Title: A Computational Analysis of Protein Sequences for Cyclophilin Superfamily using Feature Extraction
Authors: Mehra, Neha
Tiwari, Aruna
Bharill, Neha
Keywords: Bioinformatics;Computer aided diagnosis;Extraction;Feature extraction;Learning algorithms;Machine learning;Proteins;aassification;Biological sequence data;Biological techniques;Computational analysis;Feature vectors;Performance analysis;Protein sequence classification;Protein sequences;Classification (of information)
Issue Date: 2019
Publisher: Institute of Electrical and Electronics Engineers Inc.
Citation: Mehra, N., Tiwari, A., Ratnaparkhe, M. B., & Bharill, N. (2019). A computational analysis of protein sequences for cyclophilin superfamily using feature extraction. Paper presented at the Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence, SSCI 2018, 1953-1957. doi:10.1109/SSCI.2018.8628860
Abstract: Bioinformatics has emerged as one of the most challenging research area which combines machine learning and biological techniques for analysis of biological sequence data. The protein sequence classification is an important task in the field of Bioinformatics. The main aim is to process such data so that it can be made usable to be provided as input to the machine learning algorithm. In this paper, a feature extraction approach is used for converting protein sequences of cyclophilin superfamily into the feature vectors. The feature vectors are then fed as an input to three classifiers, i.e. SVM, K-NN, NB. The experimentation results are presented in the form of performance analysis of all three classifiers in terms of classification of protein sequences of cyclophilin superfamily. © 2018 IEEE.
URI: https://doi.org/10.1109/SSCI.2018.8628860
https://dspace.iiti.ac.in/handle/123456789/4599
ISBN: 9781538692769
Type of Material: Conference Paper
Appears in Collections:Department of Computer Science and Engineering

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