Analysis of RNA-Seq Data Using TEtranscripts

Methods in Molecular Biology - Transcriptome Data Analysis ◽

10.1007/978-1-4939-7710-9_11 ◽

2018 ◽

pp. 153-167 ◽

Author(s):

Ying Jin ◽

Molly Hammell

Keyword(s):

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Identification of the main venom proteins of cotton mealybug parasitoidAenasius bambawaleiHayat by RNA-Seq analysis

10.1603/ice.2016.115632 ◽

2016 ◽

Author(s):

Hoor Shaina

Keyword(s):

Rna Seq ◽

Cotton Mealybug ◽

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Integrated modeling of protein-coding genes in theManduca sextagenome using RNA-seq data from the biochemical model insect

10.1603/ice.2016.110841 ◽

2016 ◽

Author(s):

Xiaolong Cao

Keyword(s):

Integrated Modeling ◽

Rna Seq ◽

Protein Coding ◽

Protein Coding Genes ◽

Biochemical Model

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ECBN: Ensemble Clustering based on Bayesian Network inference for Single-cell RNA-seq Data

2020 39th Chinese Control Conference (CCC) ◽

10.23919/ccc50068.2020.9188589 ◽

2020 ◽

Author(s):

Dexin Zhang ◽

Yuan Zhu

Keyword(s):

Bayesian Network ◽

Single Cell ◽

Network Inference ◽

Ensemble Clustering ◽

Rna Seq ◽

Bayesian Network Inference

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Novel cell-type specific RNA-seq analysis provides new insights into the molecular processes of receptive phase endometrium and identifies sensitive biomarkers

10.26226/morressier.5912d9ead462b802923861fa ◽

2017 ◽

Author(s):

Signe Altmäe

Keyword(s):

Rna Seq ◽

Molecular Processes ◽

Cell Type ◽

Cell Type Specific

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An RNA-seq screen of P. gingivalis LPS treated human gingival fibroblasts

10.26226/morressier.5ac383172afeeb00097a3a8f ◽

2018 ◽

Author(s):

Yufeng Xie

Keyword(s):

Human Gingival Fibroblasts ◽

Gingival Fibroblasts ◽

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Nested barcode sets and sequences for the minimization of multiplexing-specific cross-contamination in RNA-Seq runs

10.26226/morressier.5ebd45acffea6f735881b1a0 ◽

2020 ◽

Author(s):

Andreas Tuerk

Keyword(s):

Cross Contamination ◽

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RNA-Seq of Dried Blood Spot Samples using Lexogen’s QuantSeq 3’ mRNA-Seq FWD assay

10.26226/morressier.5ebd45acffea6f735881b1a1 ◽

2020 ◽

Author(s):

Steve Cole

Keyword(s):

Dried Blood Spot ◽

Rna Seq ◽

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Faculty Opinions recommendation of RNA-Seq: a revolutionary tool for transcriptomics.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.1128830.793565854 ◽

2019 ◽

Author(s):

Michael Barnes

Keyword(s):

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Faculty Opinions recommendation of Full-length transcriptome assembly from RNA-Seq data without a reference genome.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.13296969.14657090 ◽

2011 ◽

Author(s):

Steven Salzberg ◽

Michael Schatz

Keyword(s):

Reference Genome ◽

Transcriptome Assembly ◽

Full Length ◽

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Faculty Opinions recommendation of Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.14267340.15779565 ◽

2012 ◽

Author(s):

Marylyn Ritchie ◽

Stephen Turner

Keyword(s):

Expression Analysis ◽

Transcript Expression ◽

Rna Seq ◽

Differential Gene

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