Evidence map›Paper›PMID 29291225›Full record

ReviewVirusdisease2017

Application of viromics: a new approach to the understanding of viral infections in humans.

Mageshbabu Ramamurthy, Sathish Sankar, Rajesh Kannangai, Balaji Nandagopal, Gopalan Sridharan

Abstract readReview
In one paragraph

Review in Virusdisease, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
–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 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
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

5 authors.

Mageshbabu RamamurthySri Sakthi Amma Institute of Biomedical Research, Sri Narayani Hospital and Research Centre, Sripuram, Vellore, Tamil Nadu 632 055 India.ORCID 0000-0003-4975-3604
Sathish SankarSri Sakthi Amma Institute of Biomedical Research, Sri Narayani Hospital and Research Centre, Sripuram, Vellore, Tamil Nadu 632 055 India.
Rajesh KannangaiDepartment of Clinical Virology, Christian Medical College and Hospital, Vellore, Tamil Nadu 632 004 India.
Balaji NandagopalSri Sakthi Amma Institute of Biomedical Research, Sri Narayani Hospital and Research Centre, Sripuram, Vellore, Tamil Nadu 632 055 India.
Gopalan SridharanSri Sakthi Amma Institute of Biomedical Research, Sri Narayani Hospital and Research Centre, Sripuram, Vellore, Tamil Nadu 632 055 India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This review is focused at exploring the strengths of modern technology driven data compiled in the areas of virus gene sequencing, virus protein structures and their implication to viral diagnosis and therapy. The information for virome analysis (viromics) is generated by the study of viral genomes (entire nucleotide sequence) and viral genes (coding for protein). Presently, the study of viral infectious diseases in terms of etiopathogenesis and development of newer therapeutics is undergoing rapid changes. Currently, viromics relies on deep sequencing, next generation sequencing (NGS) data and public domain databases like GenBank and unique virus specific databases. Two commonly used NGS platforms: Illumina and Ion Torrent, recommend maximum fragment lengths of about 300 and 400 nucleotides for analysis respectively. Direct detection of viruses in clinical samples is now evolving using these methods. Presently, there are a considerable number of good treatment options for HBV/HIV/HCV. These viruses however show development of drug resistance. The drug susceptibility regions of the genomes are sequenced and the prediction of drug resistance is now possible from 3 public domains available on the web. This has been made possible through advances in the technology with the advent of high throughput sequencing and meta-analysis through sophisticated and easy to use software and the use of high speed computers for bioinformatics. More recently NGS technology has been improved with single-molecule real-time sequencing. Here complete long reads can be obtained with less error overcoming a limitation of the NGS which is inherently prone to software anomalies that arise in the hands of personnel without adequate training. The development in understanding the viruses in terms of their genome, pathobiology, transcriptomics and molecular epidemiology constitutes viromics. It could be stated that these developments will bring about radical changes and advancement especially in the field of antiviral therapy and diagnostic virology.

Indexed as

High throughput sequencingNext generation sequencingPolymerase chain reactionVaccineViromics

Identifiers

PMID29291225
PMCPMC5747850

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.