Evidence map›Paper›PMID 28293072›Full record

ArticleBioinformation2016

An Analysis of Adenovirus Genomes Using Whole Genome Software Tools.

Padmanabhan Mahadevan

Abstract read
In one paragraph

Article in Bioinformation, 2016. 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
–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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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

1 author.

Padmanabhan MahadevanDepartment of Biology, University of Tampa, 401 W. Kennedy Blvd. Box 3F, Tampa, FL 33606.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The evolution of sequencing technology has lead to an enormous increase in the number of genomes that have been sequenced. This is especially true in the field of virus genomics. In order to extract meaningful biological information from these genomes, whole genome data mining software tools must be utilized. Hundreds of tools have been developed to analyze biological sequence data. However, only some of these tools are user-friendly to biologists. Several of these tools that have been successfully used to analyze adenovirus genomes are described here. These include Artemis, EMBOSS, pDRAW, zPicture, CoreGenes, GeneOrder, and PipMaker. These tools provide functionalities such as visualization, restriction enzyme analysis, alignment, and proteome comparisons that are extremely useful in the bioinformatics analysis of adenovirus genomes.

Indexed as

AdenovirusBioinformaticsCoreGenesGeneOrderGenomeGenomicsPercent identityRestriction enzymeSoftware

Identifiers

PMID28293072
PMCPMC5320926

What OpenQuestion holds

Textmetadata
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.