Evidence map›Paper›PMID 24659336›Full record

ReviewWorld journal of microbiology & biotechnology2014

Large-scale tag/PCR-based gene expression profiling.

Saeed Irian

Abstract readReview
PubMed Publisher
In one paragraph

Review in World journal of microbiology & biotechnology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 39% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author at 1 institution in 1 country.

Saeed Irian
Kharazmi University · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

An intriguing enigma in molecular biology is how genes within a single genome are differentially expressed in different cell types of a multicellular organism, or in response to different developmental or environmental queues in a single cell type. Quantification of transcript levels on a genome-wide scale, often termed transcript profiling, provides a powerful approach to identifying protein-coding and non-coding RNAs functionally relevant to a given biological process. Indeed, transcriptome analysis has been a key area of biological inquiry for decades and successfully produced discoveries in a multitude of processes and disease states, and in an increasingly large number of organisms. The evolution of technologies with increasing levels of informational content, ranging from hybridization-based technologies such as Northern blot analysis and microarrays to tag/polymerase chain reaction (PCR)- and sequence-based technologies including differential display and SAGE, along with the next-generation sequencing, has provided hope for revealing the molecular details of biological systems as they respond to change. This review is an overview of selected high throughput tag/PCR-based methods for genome-wide expression profiling amenable to high-throughput automated operation in any standard laboratory.

Indexed as

Gene Expression ProfilingGenomeNucleic Acid HybridizationPolymerase Chain ReactionPolymorphism, Restriction Fragment Length

Identifiers

PMID24659336
OpenAlexW2122699656

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.