Results 101 to 110 of about 588,819 (199)

Statistical calibration of qRT-PCR, microarray and RNA-Seq gene expression data with measurement error models

, 2014
The accurate quantification of gene expression levels is crucial for transcriptome study. Microarray platforms are commonly used for simultaneously interrogating thousands of genes in the past decade, and recently RNA-Seq has emerged as a promising ...
Kuczek, Thomas, Sun, Zhaonan, Zhu, Yu
core   +1 more source

Simulating multiple faceted variability in single cell RNA sequencing. [PDF]

, 2019
The abundance of new computational methods for processing and interpreting transcriptomes at a single cell level raises the need for in silico platforms for evaluation and validation.
Xu, Chenling, Yosef, Nir, Zhang, Xiuwei
core  

Single-cell total-RNA profiling unveils regulatory hubs of transcription factors

Nature Communications
Recent development of RNA velocity uses master equations to establish the kinetics of the life cycle of RNAs from unspliced RNA to spliced RNA (i.e., mature RNA) to degradation. To feed this kinetic analysis, simultaneous measurement of unspliced RNA and
Yichi Niu, Jiayi Luo, Chenghang Zong
doaj   +1 more source

RNA-seq and analysis

, 2022
RNA-seq data of T24 cells in the NC and si-Livin ...
openaire   +1 more source

Bioinformatics perspectives on transcriptomics: A comprehensive review of bulk and single‐cell RNA sequencing analyses

Quantitative Biology
The transcriptome, the complete set of RNA molecules within a cell, plays a critical role in regulating physiological processes. The advent of RNA sequencing (RNA‐seq) facilitated by Next Generation Sequencing (NGS) technologies, has revolutionized ...
Jorge A. Tzec‐Interián, Daianna González‐Padilla, Elsa B. Góngora‐Castillo   +2 more
doaj   +1 more source

Procrustes is a machine-learning approach that removes cross-platform batch effects from clinical RNA sequencing data

Communications Biology
With the increased use of gene expression profiling for personalized oncology, optimized RNA sequencing (RNA-seq) protocols and algorithms are necessary to provide comparable expression measurements between exome capture (EC)-based and poly-A RNA-seq ...
Nikita Kotlov, Kirill Shaposhnikov, Cagdas Tazearslan, Madison Chasse, Artur Baisangurov, Svetlana Podsvirova, Dawn Fernandez, Mary Abdou, Leznath Kaneunyenye, Kelley Morgan, Ilya Cheremushkin, Pavel Zemskiy, Maxim Chelushkin, Maria Sorokina, Ekaterina Belova, Svetlana Khorkova, Yaroslav Lozinsky, Katerina Nuzhdina, Elena Vasileva, Dmitry Kravchenko, Kushal Suryamohan, Krystle Nomie, John Curran, Nathan Fowler, Alexander Bagaev   +24 more
doaj   +1 more source

RNA-seq mapper

, 2014
RNA sequencing is a method for transcriptome analysis. Understanding the transcriptome is essential for various reasons such as interpreting the functional elements of the genome and undrestanding development of diseases, among many other use cases. This thesis presents a new RNA-seq spliced alignment algorithm, that uses finding the longest increasing
openaire   +1 more source

B6-RNA Seq v1

, 2019
Supplementary Table.1
openaire   +1 more source

RNA-seq analysis v1

, 2017

openaire   +1 more source

Integrated single-cell RNA-seq and bulk RNA-seq analysis to investigate key adipogenesis genes in adipose-derived stem cells. [PDF]

PLoS One
Zhang T, Cai Z, Li H, Li Z, Gan L, Mu D.
europepmc   +1 more source