Evidence map›Paper›PMID 25977299›Full record

ArticleNucleic acids research2015

ZCURVE 3.0: identify prokaryotic genes with higher accuracy as well as automatically and accurately select essential genes.

Zhi-Gang Hua, Yan Lin, Ya-Zhou Yuan, De-Chang Yang, Wen Wei, Feng-Biao Guo

Abstract read
In one paragraph

Article in Nucleic acids research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Review
  2. Article
  3. Recombineering in Non-Model Bacteria.Current protocols · 2022
    Article
  4. Review
  5. Article
  6. iRSpot-Pse6NC: Identifying recombination spots inInternational journal of biological sciences · 2018
    Article
  7. HBPred: a tool to identify growth hormone-binding proteins.International journal of biological sciences · 2018
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. 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.

Zhi-Gang HuaCenter of Bioinformatics, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 610054, China Health Big Data Science Research Center, Big Data Research Center, University of Electronic Science and Technology of China, Chengdu 610054, China Key Laboratory for NeuroInformation of the Ministry of Education, University of Electronic Science and Technology of China, Chengdu 610054, China.
Yan LinDepartment of Physics, Tianjin University, Tianjin 300072, China Key Laboratory of Systems Bioengineering, Ministry of Education, Tianjin 300072, China Collaborative Innovation Center of Chemical Science and Engineering, Tianjin 300072, China.
Ya-Zhou YuanCenter of Bioinformatics, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 610054, China Health Big Data Science Research Center, Big Data Research Center, University of Electronic Science and Technology of China, Chengdu 610054, China Key Laboratory for NeuroInformation of the Ministry of Education, University of Electronic Science and Technology of China, Chengdu 610054, China.
De-Chang YangCenter of Bioinformatics, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 610054, China Health Big Data Science Research Center, Big Data Research Center, University of Electronic Science and Technology of China, Chengdu 610054, China Key Laboratory for NeuroInformation of the Ministry of Education, University of Electronic Science and Technology of China, Chengdu 610054, China.
Wen WeiCenter of Bioinformatics, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 610054, China Health Big Data Science Research Center, Big Data Research Center, University of Electronic Science and Technology of China, Chengdu 610054, China Key Laboratory for NeuroInformation of the Ministry of Education, University of Electronic Science and Technology of China, Chengdu 610054, China.
Feng-Biao GuoCenter of Bioinformatics, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 610054, China Health Big Data Science Research Center, Big Data Research Center, University of Electronic Science and Technology of China, Chengdu 610054, China Key Laboratory for NeuroInformation of the Ministry of Education, University of Electronic Science and Technology of China, Chengdu 610054, China fbguo@uestc.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In 2003, we developed an ab initio program, ZCURVE 1.0, to find genes in bacterial and archaeal genomes. In this work, we present the updated version (i.e. ZCURVE 3.0). Using 422 prokaryotic genomes, the average accuracy was 93.7% with the updated version, compared with 88.7% with the original version. Such results also demonstrate that ZCURVE 3.0 is comparable with Glimmer 3.02 and may provide complementary predictions to it. In fact, the joint application of the two programs generated better results by correctly finding more annotated genes while also containing fewer false-positive predictions. As the exclusive function, ZCURVE 3.0 contains one post-processing program that can identify essential genes with high accuracy (generally >90%). We hope ZCURVE 3.0 will receive wide use with the web-based running mode. The updated ZCURVE can be freely accessed from http://cefg.uestc.edu.cn/zcurve/ or http://tubic.tju.edu.cn/zcurveb/ without any restrictions.

Indexed as

Genes, ArchaealGenes, BacterialSoftwareAlgorithmsGenes, EssentialGenome, ArchaealGenome, BacterialInternet

Identifiers

PMID25977299
PMCPMC4489317

What OpenQuestion holds

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Registered trials

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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.