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Circadian succession of molecular processes in living tissues

Overview of attention for article published in BMC Medical Genomics, February 2018
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Mentioned by

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2 tweeters

Citations

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1 Dimensions

Readers on

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6 Mendeley
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Title
Circadian succession of molecular processes in living tissues
Published in
BMC Medical Genomics, February 2018
DOI 10.1186/s12920-018-0325-2
Pubmed ID
Authors

Abeer Fadda, Mohammed El Anbari, Andrey Ptitsyn

Abstract

Oscillations of different origin, period and amplitude play an important role in the regulation of cellular processes. Most widely studied is the circadian or approximately daily variation in gene expression activity. Timing of gene expression is controlled by internal molecular clock keeping steady periodic expression. In this study, we shift attention towards a broad range of periodically expressed genes involved in multiple cellular functions which may or may not be under direct control of the intrinsic circadian clock. Are all molecular functions represented in expressed genes at all times? Alternatively, are different molecular functions performed at different times? Is there a pattern of succession for molecular processes and functions throughout their daily activity period? To answer these questions, we re-analyzed a number of mouse circadian gene expression data available from public sources. These data represent the normal function of metabolically active peripheral tissues (white adipose tissue, brown adipose tissue, liver). We applied novel methods for the estimation of confidence in phase assignment to identify groups of synchronous genes peaking at the same time regardless of the amplitude or the absolute intensity of expression. Each synchronous group has been annotated to identify Gene Ontology (GO) terms and molecular pathways. Our analysis identified molecular functions specific to a particular time of the day in different tissues. Improved methodology for datamining allowed for the discovery of functions and biological pathways in groups of genes with synchronized peak expression time. In particular, such functions as oxidative phase of energy metabolism, DNA repair, mRNA processing, lipid biosynthesis and others are separated in time. This timewise compartmentalization is important for understanding the cellular circuitry and can be used to optimize the time of intervention with drug or genome medication.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 2 33%
Student > Master 2 33%
Professor > Associate Professor 1 17%
Unspecified 1 17%
Readers by discipline Count As %
Engineering 3 50%
Computer Science 1 17%
Medicine and Dentistry 1 17%
Unspecified 1 17%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 06 March 2018.
All research outputs
#7,910,324
of 12,606,240 outputs
Outputs from BMC Medical Genomics
#380
of 603 outputs
Outputs of similar age
#159,947
of 271,241 outputs
Outputs of similar age from BMC Medical Genomics
#4
of 10 outputs
Altmetric has tracked 12,606,240 research outputs across all sources so far. This one is in the 23rd percentile – i.e., 23% of other outputs scored the same or lower than it.
So far Altmetric has tracked 603 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one is in the 26th percentile – i.e., 26% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 271,241 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 6 of them.