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Identification of lncRNAs from inherent features using machine learnig techniques

Publication Type : Conference Paper

Publisher : Int Conference on Bioinformatics and System Biology (BSB2018)

Source : Int Conference on Bioinformatics and System Biology (BSB2018). , IIIT Allahabad , 2018.

Campus : Coimbatore

School : School of Engineering

Department : Computer Science

Year : 2018

Abstract : Long non-coding RNAs are a distinctive class of non-coding RNAs of length greater than 200 nucleotides and no protein coding potential. LncRNA plays an important role in genetic and epigenetic regulation. Major studies reveal that IncRNAs are less conserved in their primary sequences and shows more functional characteristics at secondary structure level. The objective of this work is to identify an optimal sequencestructure combination for computational analysis of IncRNAs. We also propose a novel secondary structure quantization which consider the existence of various structure elements. The feature combinations when used as input to classification of IncRNAs from coding RNAs, significant improvement in the results were obtained.

Cite this Research Publication : S. M., Manu Madhavan, and Gopakumar G., “Identification of lncRNAs from inherent features using machine learnig techniques”, in Int Conference on Bioinformatics and System Biology (BSB2018). , IIIT Allahabad , 2018.

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