Evidence map›Paper›PMID 19173744›Full record

ArticleBMC bioinformatics2009

The Genome Reverse Compiler: an explorative annotation tool.

Andrew S Warren, João Carlos Setubal

Abstract read
In one paragraph

Article in BMC bioinformatics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
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

9 citing papers in PubMed.

  1. CNN-MGP: Convolutional Neural Networks for Metagenomics Gene Prediction.Interdisciplinary sciences, computational life sciences · 2019
    Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. 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.

Andrew S WarrenVirginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA, USA. anwarren@vt.edu
João Carlos Setubal

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAs sequencing costs have decreased, whole genome sequencing has become a viable and integral part of biological laboratory research. However, the tools with which genes can be found and functionally characterized have not been readily adapted to be part of the everyday biological sciences toolkit. Most annotation pipelines remain as a service provided by large institutions or come as an unwieldy conglomerate of independent components, each requiring their own setup and maintenance.

resultsTo address this issue we have created the Genome Reverse Compiler, an easy-to-use, open-source, automated annotation tool. The GRC is independent of third party software installs and only requires a Linux operating system. This stands in contrast to most annotation packages, which typically require installation of relational databases, sequence similarity software, and a number of other programming language modules. We provide details on the methodology used by GRC and evaluate its performance on several groups of prokaryotes using GRC's built in comparison module.

conclusionTraditionally, to perform whole genome annotation a user would either set up a pipeline or take advantage of an online service. With GRC the user need only provide the genome he or she wants to annotate and the function resource files to use. The result is high usability and a very minimal learning curve for the intended audience of life science researchers and bioinformaticians. We believe that the GRC fills a valuable niche in allowing users to perform explorative, whole-genome annotation.

Indexed as

GenomeSoftwareDatabase Management SystemsDatabases, GeneticSequence Analysis, DNA

Identifiers

PMID19173744
PMCPMC2640359

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.