ArticleMethods in molecular biology (Clifton, N.J.)2018
A Workflow Guide to RNA-seq Analysis of Chaperone Function and Beyond.
Article in Methods in molecular biology (Clifton, N.J.), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 4 citations in OpenAlex.
- Extracellular Hsp90α stimulates a unique innate gene profile in microglial cells with simultaneous activation of Nrf2 and protection from oxidative stress.Cell stress & chaperones · 2022Article
- Effects of Qi Teng Xiao Zhuo granules on circRNA expression profiles in rats with chronic glomerulonephritis.Drug design, development and therapy · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 1 country.
Funding
Abstract
RNA sequencing (RNA-seq) is a powerful method of transcript analysis that allows for the sequence identification and quantification of cellular transcripts. RNA-seq has many applications including differential gene expression (DE) analysis, gene fusion detection, allele-specific expression, isoform and splice variant quantification, and identification of novel genes. These applications can be used for downstream systems biology analyses such as gene ontology analysis to provide insights into cellular processes altered between biological conditions. Given the wide range of signaling pathways subject to chaperone activity as well as numerous chaperone functions in RNA metabolism, RNA-seq may provide a valuable tool for the study of chaperone proteins in biology and disease. This chapter outlines an example RNA-seq workflow to determine differentially expressed (DE) genes between two or more sample conditions and provides some considerations for RNA-seq experimental design.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.