Evidence map›Paper›PMID 28143396›Full record

ArticleBMC bioinformatics2017

Unsupervised detection of regulatory gene expression information in different genomic regions enables gene expression ranking.

Zohar Zafrir, Tamir Tuller

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 41% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. 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

2 authors at 1 institution in 1 country.

Zohar ZafrirDepartment of Biomedical Engineering, Tel Aviv University, P.O. Box 39040, Tel Aviv, 6997801, Israel.
Tamir TullerDepartment of Biomedical Engineering, Tel Aviv University, P.O. Box 39040, Tel Aviv, 6997801, Israel. tamirtul@post.tau.ac.il.
Tel Aviv University · IL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe regulation of all gene expression steps (e.g., Transcription, RNA processing, Translation, and mRNA Degradation) is known to be primarily encoded in different parts of genes and in genomic regions in proximity to genes (e.g., promoters, untranslated regions, coding regions, introns, etc.). However, the entire gene expression codes and the genomic regions where they are encoded are still unknown.

resultsHere, we employ an unsupervised approach to estimate the concentration of gene expression codes in different non-coding parts of genes and transcripts, such as introns and untranslated regions, focusing on three model organisms (Escherichia coli, Saccharomyces cerevisiae, and Schizosaccharomyces pombe). Our analyses support the conjecture that regions adjacent to the beginning and end of ORFs and the beginning and end of introns tend to include higher concentration of gene expression information relatively to regions further away. In addition, we report the exact regions with elevated concentration of gene expression codes. Furthermore, we demonstrate that the concentration of these codes in different genetic regions is correlated with the expression levels of the corresponding genes, and with splicing efficiency measurements and meiotic stage gene expression measurements in S. cerevisiae.

conclusionWe suggest that these discoveries improve our understanding of gene expression regulation and evolution; they can also be used for developing improved models of genome/gene evolution and for engineering gene expression in various biotechnological and synthetic biology applications.

Indexed as

AlgorithmsGene Expression RegulationEscherichia coliIntronsOpen Reading FramesRNA, MessengerSaccharomyces cerevisiaeSchizosaccharomycesUntranslated RegionsRNA, MessengerUntranslated RegionsGene expressionIntron evolutionTranscript evolution

Identifiers

PMID28143396
PMCPMC5286865
OpenAlexW2583341722

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.