Evidence map›Paper›PMID 14627837›Full record

ArticleNucleic acids research2003

Improving gene annotation of complete viral genomes.

Ryan Mills, Michael Rozanov, Alexandre Lomsadze, Tatiana Tatusova, Mark Borodovsky

Open access · bronzeAbstract read
In one paragraph

Article in Nucleic acids research, 2003. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
1.1field-weighted citation impact, top 24% 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

22 citing papers in PubMed, 48 citations in OpenAlex.

  1. Article
  2. Article
  3. A Rare, VirulentPHAGE (New Rochelle, N.Y.) · 2020
    Article
  4. Article
  5. Complete Genome Sequence ofMicrobiology resource announcements · 2019
    Article
  6. Article
  7. Article
  8. NCBI viral genomes resource.Nucleic acids research · 2015
    Article
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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

5 authors at 1 institution in 1 country.

Ryan MillsSchool of Biology, Georgia Institute of Technology, Atlanta, GA 30332-0230, USA.
Michael Rozanov
Alexandre Lomsadze
Tatiana Tatusova
Mark Borodovsky
Georgia Institute of Technology · US

Funding

PREDICTION OF GENE LOCATIONS USING STOCHASTIC MODELSR01HG000783 · NHGRI · GEORGIA INSTITUTE OF TECHNOLOGY · PI BORODOVSKY, MARK · 1993 to 2014
$4.7M
NHGRI NIH HHS HG00783NHGRI NIH HHS R01 HG000783
6 · The paper itself

Abstract

Gene annotation in viruses often relies upon similarity search methods. These methods possess high specificity but some genes may be missed, either those unique to a particular genome or those highly divergent from known homologs. To identify potentially missing viral genes we have analyzed all complete viral genomes currently available in GenBank with a specialized and augmented version of the gene finding program GeneMarkS. In particular, by implementing genome-specific self-training protocols we have better adjusted the GeneMarkS statistical models to sequences of viral genomes. Hundreds of new genes were identified, some in well studied viral genomes. For example, a new gene predicted in the genome of the Epstein-Barr virus was shown to encode a protein similar to alpha-herpesvirus minor tegument protein UL14 with heat shock functions. Convincing evidence of this similarity was obtained after only 12 PSI-BLAST iterations. In another example, several iterations of PSI-BLAST were required to demonstrate that a gene predicted in the genome of Alcelaphine herpesvirus 1 encodes a BALF1-like protein which is thought to be involved in apoptosis regulation and, potentially, carcinogenesis. New predictions were used to refine annotations of viral genomes in the RefSeq collection curated by the National Center for Biotechnology Information. Importantly, even in those cases where no sequence similarities were detected, GeneMarkS significantly reduced the number of primary targets for experimental characterization by identifying the most probable candidate genes. The new genome annotations were stored in VIOLIN, an interactive database which provides access to similarity search tools for up-to-date analysis of predicted viral proteins.

Indexed as

Genome, ViralAmino Acid SequenceComputational BiologyDatabases, GeneticGenes, ViralHerpesviridaeHumansMolecular Sequence DataSensitivity and SpecificitySequence AlignmentSoftwareViral ProteinsViral Proteins

Identifiers

PMID14627837
PMCPMC290248
OpenAlexW2044042656

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.