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Noncoding RNAs and their annotation using metagenomics algorithms
Author(s) -
Ray Shubhra Sankar,
Maiti Sonam
Publication year - 2015
Publication title -
wiley interdisciplinary reviews: data mining and knowledge discovery
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.506
H-Index - 47
eISSN - 1942-4795
pISSN - 1942-4787
DOI - 10.1002/widm.1142
Subject(s) - metagenomics , computer science , context (archaeology) , annotation , relevance (law) , non coding rna , computational biology , artificial intelligence , machine learning , biology , rna , gene , genetics , paleontology , political science , law
This article provides an overview of noncoding RNAs ( ncRNA ) involving their structure, function, computational methods for structure prediction and the algorithms for analyzing ncRNAs from metagenome samples. Different techniques for ncRNA structure prediction such as dynamic programming ( DP ), genetic algorithm ( GA ), artificial neural network ( ANN ) and stochastic context‐free grammar ( SCFG ) are discussed. The basic concepts of metagenomics along with their biological basis are mentioned and the relevance of ncRNAs in metagenomics is also explored. Similarity and composition based computational methods for analyzing noncoding sequences in metagenomes are then mentioned along with their biological findings. An extensive bibliography is included. WIREs Data Mining Knowl Discov 2015, 5:1–20. doi: 10.1002/widm.1142 Conflict of interest: The authors have declared no conflicts of interest for this article. This article is categorized under: Algorithmic Development > Biological Data Mining Algorithmic Development > Structure Discovery Application Areas > Science and Technology