About: Profiling and Searching for RNA Pseudoknot Structures in Genomes

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An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Profiling and Searching for RNA Pseudoknot Structures in Genomes
Creator	Cai, Liming Liu, Chunmei Malmberg, Russell Song, Yinglei
Source	PMC
abstract	We developed a new method that can profile and efficiently search for pseudoknot structures in noncoding RNA genes. It profiles interleaving stems in pseudoknot structures with independent Covariance Model (CM) components. The statistical alignment score for searching is obtained by combining the alignment scores from all CM components. Our experiments show that the model can achieve excellent accuracy on both random and biological data. The efficiency achieved by the method makes it possible to search for structures that contain pseudoknot in genomes of a variety of organisms.
has issue date	2005-01-01(xsd:dateTime)
bibo:doi	10.1007/11567752_2
has license	no-cc
sha1sum (hex)	5a7d78d4e4a9d3f9487576d7abfaa23ee1b503b3
schema:url	https://doi.org/10.1007/11567752_2
resource representing a document's title	Profiling and Searching for RNA Pseudoknot Structures in Genomes
has PubMed Central identifier	PMC7120494
schema:publication	Transactions on Computational Systems Biology II
resource representing a document's body	covid:5a7d78d4e4a9d3f9487576d7abfaa23ee1b503b3#body_text
is schema:about of	named entity 'excellent' named entity 'efficiently' named entity 'Pseudoknot' named entity 'MODEL' named entity 'OBTAINED BY' named entity 'STRUCTURES' named entity 'OUR' named entity 'SCORES' named entity 'METHOD' named entity 'STATISTICAL' named entity 'CONTAIN' named entity 'EFFICIENCY' named entity 'PROFILE' named entity 'COVARIANCE' named entity 'GENOMES' named entity 'RNA' named entity 'VARIETY' named entity 'ACCURACY' named entity 'INDEPENDENT' named entity 'PSEUDOKNOT' named entity 'ORGANISMS' named entity 'PSEUDOKNOT' named entity 'POSSIBLE' named entity 'COMPONENTS' named entity 'SCORE' named entity 'GENES' named entity 'NEW' named entity 'EXPERIMENTS' named entity 'SEARCH' named entity 'STRUCTURES' named entity 'GENOMES' named entity 'BIOLOGICAL DATA' named entity 'ALIGNMENT' named entity 'RANDOM' named entity 'COMBINING' named entity 'STEMS' named entity 'NONCODING RNA' named entity 'EXCELLENT' covid:arg/5a7d78d4e4a9d3f9487576d7abfaa23ee1b503b3 named entity 'efficiency' named entity 'The' named entity 'pseudoknot' named entity 'score' named entity 'structures' named entity 'pseudoknot' named entity 'genomes' named entity 'RNA' named entity 'Neisseria meningitidis' named entity 'database' named entity 'genomes' named entity 'genomes' named entity 'SCFG' named entity 'nucleotides' named entity 'multiple alignment' named entity 'Covariance' named entity 'RNA sequence' named entity 'nucleotides' named entity 'elongation factor P-TEFb' named entity 'nucleotides' named entity 'messenger RNAs' named entity 'base pairs' named entity 'dynamic programming' named entity 'random sequence' named entity 'nucleotide bases' named entity 'multiple alignments' named entity 'matrices' named entity 'log-odds' named entity 'log-odds' named entity '3' untranslated region' named entity 'peptide' named entity 'gene' named entity 'base pairs' named entity 'base pairs' named entity 'nucleotides' named entity 'noncoding RNA' named entity 'CYK algorithm' named entity 'undirected graph' named entity 'base pairs' named entity 'bacterial genome' named entity 'conformation'

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