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Identification of species based on DNA barcode using k-mer feature vector and Random forest classifier

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Title Identification of species based on DNA barcode using k-mer feature vector and Random forest classifier
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Creator Prabina Kumar Meher
Tanmaya Kumar Sahu
A R Rao
 
Subject BOLD systems
DNA barcode
Oligomer frequency
Random forest
SPIDBAR
 
Description Not Available
DNA barcoding is a molecular diagnostic method that allows automated and accurate identification of species based on a short and standardized fragment of DNA. To this end, an attempt has been made in this study to develop a computational approach for identifying the species by comparing its barcode with the barcode sequence of known species present in the reference library. Each barcode sequence was first mapped onto a numeric feature vector based on k-mer frequencies and then Random forest methodology was employed on the transformed dataset for species identification. The proposed approach outperformed similarity-based, tree-based, diagnostic-based approaches and found comparable with existing supervised learning based approaches in terms of species identification success rate, while compared using real and simulated datasets. Based on the proposed approach, an online web interface SPIDBAR has also been developed and made freely available at http://cabgrid.res.in:8080/spidbar/ for species identification by the taxonomists.
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Date 2022-08-07T06:13:32Z
2022-08-07T06:13:32Z
2016-11-05
 
Type Research Paper
 
Identifier Meher PK, Sahu TK, Rao AR. (2016). Identification of species based on DNA barcode using k-mer feature vector and Random forest classifier. Gene.;592(2):316-24. doi: 10.1016/j.gene.2016.07.010. Epub 2016 Jul 5. PMID: 27393648.
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http://krishi.icar.gov.in/jspui/handle/123456789/73731
 
Language English
 
Relation Not Available;
 
Publisher Not Available