Evidence map›Paper›PMID 19651192›Full record

ArticleGene2009

Simple and fast classification of non-LTR retrotransposons based on phylogeny of their RT domain protein sequences.

Vladimir V Kapitonov, Sébastien Tempel, Jerzy Jurka

Abstract readEvaluation Study
In one paragraph

Article in Gene, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 64 papers.

0numbers the graph read from it
0cells of the map it votes in
64citing 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

64 citing papers in PubMed.

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4 more citing papers are in PubMed but not listed here.

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

3 authors.

Vladimir V KapitonovGenetic Information Research Institute, 1925 Landings Dr, Mountain View, CA 94041, USA. vladimir@girinst.org
Sébastien Tempel
Jerzy Jurka

Funding

Rephase Update-a Database of Repetitive SequencesP41LM006252 · NLM · GENETIC INFORMATION RESEARCH INSTITUTE · PI JURKA, JERZY WLADYSLAW · 1996 to 2013
$6.0M
NLM NIH HHS 5 P41 LM006252NLM NIH HHS P41 LM006252
6 · The paper itself

Abstract

Rapidly growing number of sequenced genomes requires fast and accurate computational tools for analysis of different transposable elements (TEs). In this paper we focus on a rapid and reliable procedure for classification of autonomous non-LTR retrotransposons based on alignment and clustering of their reverse transcriptase (RT) domains. Typically, the RT domain protein sequences encoded by different non-LTR retrotransposons are similar to each other in terms of significant BLASTP E-values. Therefore, they can be easily detected by the routine BLASTP searches of genomic DNA sequences coding for proteins similar to the RT domains of known non-LTR retrotransposons. However, detailed classification of non-LTR retrotransposons, i.e. their assignment to specific clades, is a slow and complex procedure that is not formalized or integrated as a standard set of computational methods and data. Here we describe a tool (RTclass1) designed for the fast and accurate automated assignment of novel non-LTR retrotransposons to known or novel clades using phylogenetic analysis of the RT domain protein sequences. RTclass1 classifies a particular non-LTR retrotransposon based on its RT domain in less than 10 min on a standard desktop computer and achieves 99.5% accuracy. RT1class1 works either as a stand-alone program installed locally or as a web-server that can be accessed distantly by uploading sequence data through the internet (http://www.girinst.org/RTphylogeny/RTclass1).

Indexed as

PhylogenyRetroelementsAlgorithmsAmino Acid SequenceClassificationModels, GeneticProtein Structure, TertiaryReproducibility of ResultsRNA-Directed DNA PolymeraseSequence Analysis, DNATerminal Repeat SequencesRetroelementsRNA-Directed DNA Polymerase

Identifiers

PMID19651192
PMCPMC2829327

What OpenQuestion holds

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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.