Evidence map›Paper›PMID 22022467›Full record

ArticlePloS one2011

HIVsirDB: a database of HIV inhibiting siRNAs.

Atul Tyagi, Firoz Ahmed, Nishant Thakur, Arun Sharma, Gajendra P S Raghava, Manoj Kumar

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
1.3field-weighted citation impact, top 20% 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

23 citing papers in PubMed, 40 citations in OpenAlex.

  1. Review
  2. Review
  3. Review
  4. Article
  5. Article
  6. Review
  7. Article
  8. A review on current status of antiviral siRNA.Reviews in medical virology · 2018
    Review
  9. PVsiRNAdb: a database for plant exclusive virus-derived small interfering RNAs.Database : the journal of biological databases and curation · 2018
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. The macrophage: a therapeutic target in HIV-1 infection.Molecular and cellular therapies · 2014
    Review
  18. Article
  19. Article
  20. 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

6 authors at 1 institution in 1 country.

Atul TyagiBioinformatics Centre, Institute of Microbial Technology (CSIR), Chandigarh, India.
Firoz Ahmed
Nishant Thakur
Arun Sharma
Gajendra P S Raghava
Manoj Kumar
Institute of Microbial Technology · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHuman immunodeficiency virus (HIV) is responsible for millions of deaths every year. The current treatment involves the use of multiple antiretroviral agents that may harm patients due to their toxic nature. RNA interference (RNAi) is a potent candidate for the future treatment of HIV, uses short interfering RNA (siRNA/shRNA) for silencing HIV genes. In this study, attempts have been made to create a database HIVsirDB of siRNAs responsible for silencing HIV genes. DESCRIPTIONS: HIVsirDB is a manually curated database of HIV inhibiting siRNAs that provides comprehensive information about each siRNA or shRNA. Information was collected and compiled from literature and public resources. This database contains around 750 siRNAs that includes 75 partially complementary siRNAs differing by one or more bases with the target sites and over 100 escape mutant sequences. HIVsirDB structure contains sixteen fields including siRNA sequence, HIV strain, targeted genome region, efficacy and conservation of target sequences. In order to facilitate user, many tools have been integrated in this database that includes; i) siRNAmap for mapping siRNAs on target sequence, ii) HIVsirblast for BLAST search against database, iii) siRNAalign for aligning siRNAs.

conclusionHIVsirDB is a freely accessible database of siRNAs which can silence or degrade HIV genes. It covers 26 types of HIV strains and 28 cell types. This database will be very useful for developing models for predicting efficacy of HIV inhibiting siRNAs. In summary this is a useful resource for researchers working in the field of siRNA based HIV therapy. HIVsirDB database is accessible at http://crdd.osdd.net/raghava/hivsir/.

Indexed as

Databases, GeneticBase SequenceComputational BiologyHIVInternetMolecular Sequence DataRNA, Small InterferingSearch EngineRNA, Small Interfering

Identifiers

PMID22022467
PMCPMC3191155
OpenAlexW2060109322

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.