Evidence map›Paper›PMID 21641563›Full record

ArticleGenomics, proteomics & bioinformatics2011

TAAPP: Tiling Array Analysis Pipeline for Prokaryotes.

Ranjit Kumar, Shane C Burgess, Mark L Lawrence, Bindu Nanduri

Open access · goldAbstract read
In one paragraph

Article in Genomics, proteomics & bioinformatics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.3field-weighted citation impact, top 42% 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

3 citing papers in PubMed, 3 citations in OpenAlex.

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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

4 authors at 2 institutions in 1 country.

Ranjit KumarCollege of Veterinary Medicine, Mississippi State University, MS 39762, USA. rkumar@cvm.msstate.edu
Shane C Burgess
Mark L Lawrence
Bindu Nanduri
Biocom · USMississippi State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

High-density tiling arrays provide closer view of transcription than regular microarrays and can also be used for annotating functional elements in genomes. The identified transcripts usually have a complex overlapping architecture when compared to the existing genome annotation. Therefore, there is a need for customized tiling array data analysis tools. Since most of the initial tiling arrays were conducted in eukaryotes, data analysis methods are well suited for eukaryotic genomes. For using whole-genome tiling arrays to identify previously unknown transcriptional elements like small RNA and antisense RNA in prokaryotes, existing data analysis tools need to be tailored for prokaryotic genome architecture. Furthermore, automation of such custom data analysis workflow is necessary for biologists to apply this powerful platform for knowledge discovery. Here we describe TAAPP, a web-based package that consists of two modules for prokaryotic tiling array data analysis. The transcript generation module works on normalized data to generate transcriptionally active regions (TARs). The feature extraction and annotation module then maps TARs to existing genome annotation. This module further categorizes the transcription profile into potential novel non-coding RNA, antisense RNA, gene expression and operon structures. The implemented workflow is microarray platform independent and is presented as a web-based service. The web interface is freely available for academic use at http://lims.lsbi.mafes.msstate.edu/TAAPP-HTML/.

Indexed as

Gene Expression ProfilingSoftwareDNA, ComplementaryMolecular Sequence AnnotationOligonucleotide Array Sequence AnalysisOperonRegulatory Elements, TranscriptionalRNA, UntranslatedStreptococcus pneumoniaeDNA, ComplementaryRNA, Untranslated

Identifiers

PMID21641563
PMCPMC5054164
OpenAlexW2027975062

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.