Evidence map›Paper›PMID 17597916›Full record

ArticleBioinformation2006

Functional annotation of hypothetical proteins - A review.

Selvarajan Sivashankari, Piramanayagam Shanmughavel

Open access · hybridAbstract read
In one paragraph

Article in Bioinformation, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed, 1 pooled it
1.6field-weighted citation impact, top 18% 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

42 citing papers in PubMed, 1 synthesis or guideline pooled it, 115 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. ACS omega · 2025
    Article
  8. Article
  9. Analysis of Whole-Genome for Identification of SevenInternational journal of molecular sciences · 2024
    Article
  10. Article
  11. Article
  12. Structure of the hypothetical protein TTHA1873 from Thermus thermophilus.Acta crystallographica. Section F, Structural biology communications · 2022
    Article
  13. Review
  14. Article
  15. Functional Annotation from Structural Homology.Methods in molecular biology (Clifton, N.J.) · 2022
    Article
  16. Frontiers in genetics · 2022
    Article
  17. Review
  18. Article
  19. Amino Acid Composition in Various Types of Nucleic Acid-Binding Proteins.International journal of molecular sciences · 2021
    Review
  20. Deciphering the functional role of hypothetical proteins fromMolecular biology research communications · 2020
    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

2 authors at 1 institution in 1 country.

Selvarajan SivashankariDepartment of Bioinformatics, Kongunadu arts and science college, Coimbatore - 641029, India.
Piramanayagam Shanmughavel
Bharathiar University · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The complete human genome sequences in the public database provide ways to understand the blue print of life. As of June 29, 2006, 27 archaeal, 326 bacterial and 21 eukaryotes is complete genomes are available and the sequencing for 316 bacterial, 24 archaeal, 126 eukaryotic genomes are in progress. The traditional biochemical/molecular experiments can assign accurate functions for genes in these genomes. However, the process is time-consuming and costly. Despite several efforts, only 50-60 % of genes have been annotated in most completely sequenced genomes. Automated genome sequence analysis and annotation may provide ways to understand genomes. Thus, determination of protein function is one of the challenging problems of the post-genome era. This demands bioinformatics to predict functions of un-annotated protein sequences by developing efficient tools. Here, we discuss some of the recent and popular approaches developed in Bioinformatics to predict functions for hypothetical proteins.

Identifiers

PMID17597916
PMCPMC1891709
OpenAlexW2044734766

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.