Tag Archives: transcriptome sequencing

Transcriptome Sequenced – Populus tomentosa

rna-seq

Wood formation affects the chemical and physical properties of wood, and thus affects its utility as a building material or a feedstock for biofuels, pulp and paper. To obtain genome-wide insights on the transcriptome changes and regulatory networks in wood ...

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Choosing a next-generation sequencing pipeline

rna-seq

The next-generation sequencing (NGS) technologies are revolutionary tools which have made possible achieving remarkable advances in genetics since the beginning of the twenty-first century. Thanks to the possibility to produce large amount of sequence data, these tools are going to ...

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PLEK: a tool for predicting long non-coding RNAs and messenger RNAs based on an improved k-mer scheme

rna-seq

High-throughput transcriptome sequencing (RNA-seq) technology promises to discover novel protein-coding and non-coding transcripts, particularly the identification of long non-coding RNAs (lncRNAs) from de novo sequencing data. This requires tools that are not restricted by prior gene annotations, genomic sequences and ...

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Transcriptome Sequencing reveals that species diversity is predictable

rna-seq

Genetic diversity is the amount of variation observed between DNA sequences from distinct individuals of a given species. This pivotal concept of population genetics has implications for species health, domestication, management and conservation. Levels of genetic diversity seem to vary ...

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Transcriptome sequencing uncovers altered long intergenic non-coding RNAs

Long intergenic non-coding RNAs (lncRNAs) represent an emerging and under-studied class of transcripts that play a significant role in human cancers. Due to the tissue- and cancer-specific expression patterns observed for many lncRNAs it is believed that they could serve ...

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An integrative method to normalize RNA-Seq data

rna-seq

Transcriptome sequencing is a powerful tool for measuring gene expression, but as well as some other technologies, various artifacts and biases affect the quantification. In order to correct some of them, several normalization approaches have emerged, differing both in the ...

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