Results 181 to 190 of about 345,547 (215)

RNA-Seq in the Collaborative Cross

2016
The Collaborative Cross (CC) is a large panel of inbred mouse strains currently being developed for multiple areas of research. Scientists are taking integrated omics-style approaches to collecting data in order to obtain a deeper understanding of the biological mechanisms underlying a number of diverse disease phenotypes.
Martin T. Ferris, Courtney Wilkins, Richard Green, Michael Gale   +3 more
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RNA-seq in Skeletal Biology

Current Osteoporosis Reports, 2019
The goal of this paper is to review state-of-the-art transcriptome profiling methods and their recent applications in the field of skeletal biology.Next-generation sequencing of mRNA (RNA-seq) methods have been established and routinely used in skeletal biology research.
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Computational Analysis of RNA-seq

2012
Using High-Throughput DNA Sequencing (HTS) to examine gene expression is rapidly becoming a -viable choice and is typically referred to as RNA-seq. Often the depth and breadth of coverage of RNA-seq data can exceed what is achievable using microarrays. However, the strengths of RNA-seq are often its greatest weaknesses.
William G. Spollen, Christopher A. Bottoms, Scott A. Givan   +2 more
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Transcriptome Sequencing: RNA-Seq

2018
RNA sequencing (RNA-seq) can not only be used to identify the expression of common or rare transcripts but also in the identification of other abnormal events, such as alternative splicing, novel transcripts, and fusion genes. In principle, RNA-seq can be carried out by almost all of the next-generation sequencing (NGS) platforms, but the libraries of ...
Hong Zhang, Lin He, Lei Cai
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Complete Transcriptome RNA-Seq

2016
RNA-Seq is the leading technology for analyzing gene expression on a global scale across a broad spectrum of sample types. However, due to chemical modifications by fixation or degradation due to collection methods, samples often contain an abundance of RNA that is no longer intact, and the capability of current RNA-Seq protocols to accurately quantify
David Frankhouser, Cameron L. Stump, Scott D. Michaels, Aaron Buechlein, Yunlong Liu, Haixu Tang, Douglas B. Rusch, Fang Fang, Tim H M Huang, James Ford, Jeremy Chien, Kenneth P. Nephew, Pearlly S. Yan, Daniela Matei, Paige A. Stump, David F.B. Miller, Karl Kroll   +16 more
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RNA seq data

2018
RNA seq ...
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Transcriptomics in the RNA-seq era

Current Opinion in Chemical Biology, 2013
The transcriptomics field has developed rapidly with the advent of next-generation sequencing technologies. RNA-seq has now displaced microarrays as the preferred method for gene expression profiling. The comprehensive nature of the data generated has been a boon in terms of transcript identification but analysis challenges remain.
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Analysis RNA-seq and Noncoding RNA

2016
RNA-Seq is an approach to transcriptome profiling that uses deep-sequencing technologies to detect and accurately quantify RNA molecules originating from a genome at a given moment in time. In recent years, the advent of RNA-Seq has facilitated genome-wide expression profiling, including the identification of novel and rare transcripts like noncoding ...
A. Arrigoni, V. Ranzani, G. Rossetti, I. Panzeri, S. Abrignani, R. J. P. Bonnal, M. Pagani   +6 more
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Transcriptome Analysis Using RNA-Seq

2012
Transcriptome analysis by next-generation sequencing (RNA-seq) allows investigation of a transcriptome at unsurpassed resolution. One major benefit is that RNA-seq is independent of a priori knowledge on the sequence under investigation, thereby also allowing analysis of poorly characterized Plasmodium species.
Hoeijmakers, W.A.M., Bartfai, R.C., Stunnenberg, H.   +2 more
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RNA-Seq Data Analysis

RNA-Seq data analysis stands as a vital part of genomics research, turning vast and complex datasets into meaningful biological insights. It is a field marked by rapid evolution and ongoing innovation, necessitating a thorough understanding for anyone seeking to unlock the potential of RNA-Seq data.
James, Li, Rency S, Varghese, Habtom W, Ressom   +2 more
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