Results 11 to 20 of about 1,742,697 (207)
RNA Sequencing Analysis of Salivary Extracellular RNA [PDF]
, 2016 Salivary biomarkers for disease detection, diagnostic and prognostic assessments have become increasingly well established in recent years. In this chapter we explain the current leading technology that has been used to characterize salivary non-coding RNAs (ncRNAs) from the extracellular RNA (exRNA) fraction: HiSeq from Illumina® platform for RNA ...
Majem, Blanca +3 more
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Deciphering the RRM-RNA recognition code: A computational analysis.
PLoS Computational Biology, 2023 RNA recognition motifs (RRM) are the most prevalent class of RNA binding domains in eucaryotes. Their RNA binding preferences have been investigated for almost two decades, and even though some RRM domains are now very well described, their RNA ...
Joel Roca-Martínez +3 more
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Informatics in Medicine Unlocked, 2021 RNA binding proteins are involved in many functions, though the majority of them are composed into small RNA binding domains. The S15/NS1 RNA binding domain is a ribosomal S15 and the non-structural NS1 protein. In this study, an attempt was made to find
S. Muthu Krishnan
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Circular RNA Expression Profiles in Nasopharyngeal Carcinoma by Sequence Analysis
Frontiers in Oncology, 2020 Circular RNAs (circRNAs), as a burgeoning sort of non-coding RNAs (ncRNAs), can regulate the expression of parental genes as miRNA sponges. This study was designed to explore the circRNA expression profile of nasopharyngeal carcinoma (NPC).
Jing Yang +7 more
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Big Data Analytics in RNA-sequencing
Korean Journal of Clinical Laboratory Science, 2023 As next-generation sequencing has been developed and used widely, RNA-sequencing (RNA-seq) has rapidly emerged as the first choice of tools to validate global transcriptome profiling.
Sung-Hun WOO, Byung Chul JUNG
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SePIA: RNA and small RNA sequence processing, integration, and analysis [PDF]
BioData Mining, 2016 Large-scale sequencing experiments are complex and require a wide spectrum of computational tools to extract and interpret relevant biological information. This is especially true in projects where individual processing and integrated analysis of both small RNA and complementary RNA data is needed.
Icay, Katherine +5 more
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TT2NE: A novel algorithm to predict RNA secondary structures with pseudoknots [PDF]
, 2010 We present TT2NE, a new algorithm to predict RNA secondary structures with pseudoknots. The method is based on a classification of RNA structures according to their topological genus.
Bailor +29 more
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mRNA vaccine quality analysis using RNA sequencing
Nature Communications, 2023 Abstract The success of mRNA vaccines has been realised, in part, by advances in manufacturing that enabled billions of doses to be produced at sufficient quality and safety. However, mRNA vaccines must be rigorously analysed to measure their integrity and detect contaminants that reduce their effectiveness and induce side-effects. Currently,
Helen M. Gunter +15 more
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A Robust and Precise ConvNet for Small Non-Coding RNA Classification (RPC-snRC)
IEEE Access, 2021 Small non-coding RNAs (ncRNAs) are attracting increasing attention as they are now considered potentially valuable resources in the development of new drugs intended to cure several human diseases.
Muhammad Nabeel Asim +5 more
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RNA sequence analysis using covariance models
Nucleic Acids Research, 1994 We describe a general approach to several RNA sequence analysis problems using probabilistic models that flexibly describe the secondary structure and primary sequence consensus of an RNA sequence family. We call these models 'covariance models'. A covariance model of tRNA sequences is an extremely sensitive and discriminative tool for searching for ...
S R, Eddy, R, Durbin
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