↓ Skip to main content

PIPE-chipSAD: A Pipeline for the Analysis of High Density Arrays of Bacterial Transcriptomes

Overview of attention for article published in Frontiers in Molecular Biosciences, December 2016
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
2 X users

Readers on

mendeley
5 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
PIPE-chipSAD: A Pipeline for the Analysis of High Density Arrays of Bacterial Transcriptomes
Published in
Frontiers in Molecular Biosciences, December 2016
DOI 10.3389/fmolb.2016.00082
Pubmed ID
Authors

Silvia Bottini, Elena Del Tordello, Luca Fagnocchi, Claudio Donati, Alessandro Muzzi

Abstract

PIPE-chipSAD is a pipeline for bacterial transcriptome studies based on high-density microarray experiments. The main algorithm chipSAD, integrates the analysis of the hybridization signal with the genomic position of probes and identifies portions of the genome transcribing for mRNAs. The pipeline includes a procedure, align-chipSAD, to build a multiple alignment of transcripts originating in the same locus in multiple experiments and provides a method to compare mRNA expression across different conditions. Finally, the pipeline includes anno-chipSAD a method to annotate the detected transcripts in comparison to the genome annotation. Overall, our pipeline allows transcriptional profile analysis of both coding and non-coding portions of the chromosome in a single framework. Importantly, due to its versatile characteristics, it will be of wide applicability to analyse, not only microarray signals, but also data from other high throughput technologies such as RNA-sequencing. The current PIPE-chipSAD implementation is written in Python programming language and is freely available at https://github.com/silviamicroarray/chipSAD.

Timeline

Login to access the full chart related to this output.

If you don’t have an account, click here to discover Explorer

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 40%
Student > Bachelor 2 40%
Student > Ph. D. Student 1 20%
Professor > Associate Professor 1 20%
Readers by discipline Count As %
Engineering 2 40%
Agricultural and Biological Sciences 1 20%
Biochemistry, Genetics and Molecular Biology 1 20%
Immunology and Microbiology 1 20%
Computer Science 1 20%
Other 0 0%
Attention Score in Context

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 09 March 2017.
All research outputs
#17,837,681
of 22,914,829 outputs
Outputs from Frontiers in Molecular Biosciences
#1,685
of 3,821 outputs
Outputs of similar age
#293,383
of 420,738 outputs
Outputs of similar age from Frontiers in Molecular Biosciences
#9
of 21 outputs
Altmetric has tracked 22,914,829 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,821 research outputs from this source. They receive a mean Attention Score of 3.3. This one is in the 48th percentile – i.e., 48% 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 420,738 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 21 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.