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Background: Since the invention of next-generation RNA sequencing (RNA-seq) technologies, they have become a powerful tool to study the presence and quantity of RNA molecules in biological samples and have revolutionized transcriptomic…

Genomics · Quantitative Biology 2021-12-01 Wei Vivian Li , Jingyi Jessica Li

RNA sequencing (RNA-seq) has been rapidly adopted for the profiling of transcriptomes in many areas of biology, including studies into gene regulation, development and disease. Of particular interest is the discovery of differentially…

Single-cell RNA-sequencing (scRNA-seq) has become a routinely used technique to quantify the gene expression profile of thousands of single cells simultaneously. Analysis of scRNA-seq data plays an important role in the study of cell states…

Genomics · Quantitative Biology 2022-10-13 Matthew Brendel , Chang Su , Zilong Bai , Hao Zhang , Olivier Elemento , Fei Wang

Recently, ultra high-throughput sequencing of RNA (RNA-Seq) has been developed as an approach for analysis of gene expression. By obtaining tens or even hundreds of millions of reads of transcribed sequences, an RNA-Seq experiment can offer…

Methodology · Statistics 2011-06-17 Julia Salzman , Hui Jiang , Wing Hung Wong

The ability to measure the transcriptomes of single cells has only been feasible for a few years, and is becoming an extremely popular assay. While many types of analysis and questions can be answered using single cell RNA-sequencing, a…

Genomics · Quantitative Biology 2017-08-09 Valentine Svensson , Roser Vento-Tormo , Sarah A Teichmann

RNA-Seq analysis has revolutionized researchers' understanding of the transcriptome in biological research. Assessing the differences in transcriptomic profiles between tissue samples or patient groups enables researchers to explore the…

The development of novel high-throughput sequencing (HTS) methods for RNA (RNA-Seq) has provided a very powerful mean to study splicing under multiple conditions at unprecedented depth. However, the complexity of the information to be…

Genomics · Quantitative Biology 2015-08-03 Gael P. Alamancos , Eneritz Agirre , Eduardo Eyras

In recent years, the advances in single-cell RNA-seq techniques have enabled us to perform large-scale transcriptomic profiling at single-cell resolution in a high-throughput manner. Unsupervised learning such as data clustering has become…

Genomics · Quantitative Biology 2020-01-07 Shixiong Zhang , Xiangtao Li , Qiuzhen Lin , Ka-Chun Wong

Single-cell RNA sequencing (scRNA-seq) has revolutionized our ability to analyze gene expression at the resolution of individual cells, providing unprecedented insights into cellular heterogeneity and complex biological systems. This paper…

Other Quantitative Biology · Quantitative Biology 2024-06-11 Megha Patel , Nimish Magre , Himanshi Motwani , Nik Bear Brown

Alternative splicing is crucial in gene regulation, with significant implications in clinical settings and biotechnology. This review article compiles bioinformatics RNA-seq tools for investigating differential splicing; offering a detailed…

Genomics · Quantitative Biology 2024-09-10 Ben J Draper , Mark J Dunning , David C James

The newly developed deep-sequencing technologies make it possible to acquire both quantitative and qualitative information regarding transcript biology. By measuring messenger RNA levels for all genes in a sample, RNA-seq provides an…

Genomics · Quantitative Biology 2014-12-05 Lerong Li , Momiao Xiong

High-throughput RNA sequencing (RNA-seq) is now the standard method to determine differential gene expression. Identifying differentially expressed genes crucially depends on estimates of read count variability. These estimates are…

RNA-Seq is rapidly becoming the standard technology for transcriptome analysis. Fundamental to many of the applications of RNA-Seq is the quantification problem, which is the accurate measurement of relative transcript abundances from the…

Genomics · Quantitative Biology 2011-05-16 Lior Pachter

Rapid advancements in high-throughput single-cell RNA-seq (scRNA-seq) technologies and experimental protocols have led to the generation of vast amounts of genomic data that populates several online databases and repositories. Here, we…

Genomics · Quantitative Biology 2024-04-17 Mahnoor N. Gondal , Saad Ur Rehman Shah , Arul M. Chinnaiyan , Marcin Cieslik

High-throughput sequencing of RNA transcripts (RNA-seq) has become the method of choice for detection of differential expression (DE). Concurrent with the growing popularity of this technology there has been a significant research effort…

RNA sequencing (RNA-seq) is the conventional genome-scale approach used to capture the expression levels of all detectable genes in a biological sample. This is now regularly used for population-based studies designed to identify genetic…

Genomics · Quantitative Biology 2026-05-25 Christopher Thron , Farhad Jafari

Single-cell RNA sequencing (scRNA-seq) provides a high throughput, quantitative and unbiased framework for scientists in many research fields to identify and characterize cell types within heterogeneous cell populations from various…

Quantitative Methods · Quantitative Biology 2022-09-28 Yeganeh Madadi , Aboozar Monavarfeshani , Hao Chen , W. Daniel Stamer , Robert W. Williams , Siamak Yousefi

RNA sequencing techniques, like bulk RNA-seq and Single Cell (sc) RNA-seq, are critical tools for the biologist looking to analyze the genetic activity/transcriptome of a tissue or cell during an experimental procedure. Platforms like…

Genomics · Quantitative Biology 2024-07-08 Devam Mondal , Atharva Inamdar

Noncoding RNAs are integral to a wide range of biological processes, including translation, gene regulation, host-pathogen interactions and environmental sensing. While genomics is now a mature field, our capacity to identify noncoding RNA…

RNAs are essential molecules that carry genetic information vital for life, with profound implications for drug development and biotechnology. Despite this importance, RNA research is often hindered by the vast literature available on the…

Genomics · Quantitative Biology 2024-11-15 Yijia Xiao , Edward Sun , Yiqiao Jin , Wei Wang
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