Evidence map›Paper›PMID 31362694›Full record

ArticleBMC bioinformatics2019

IRESpy: an XGBoost model for prediction of internal ribosome entry sites.

Junhui Wang, Michael Gribskov

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed
3.3field-weighted citation impact, top 7% 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

45 citing papers in PubMed, 71 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Review
  11. Article
  12. Article
  13. Review
  14. Article
  15. PML Body Biogenesis: A Delicate Balance of Interactions.International journal of molecular sciences · 2023
    Review
  16. Article
  17. Article
  18. Article
  19. Review
  20. LBCE-XGB: A XGBoost Model for Predicting Linear B-Cell Epitopes Based on BERT Embeddings.Interdisciplinary sciences, computational life sciences · 2023
    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.

Junhui WangBiological Sciences Department, Purdue University, West Lafayette, IN, USA.
Michael GribskovBiological Sciences Department, Purdue University, West Lafayette, IN, USA. mgribsko@purdue.edu.ORCID http://orcid.org/0000-0002-1718-0242
Purdue University West Lafayette · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundInternal ribosome entry sites (IRES) are segments of mRNA found in untranslated regions that can recruit the ribosome and initiate translation independently of the 5' cap-dependent translation initiation mechanism. IRES usually function when 5' cap-dependent translation initiation has been blocked or repressed. They have been widely found to play important roles in viral infections and cellular processes. However, a limited number of confirmed IRES have been reported due to the requirement for highly labor intensive, slow, and low efficiency laboratory experiments. Bioinformatics tools have been developed, but there is no reliable online tool.

resultsThis paper systematically examines the features that can distinguish IRES from non-IRES sequences. Sequence features such as kmer words, structural features such as Q

conclusionsIRESpy is a fast, reliable, high-throughput IRES online prediction tool. It provides a publicly available tool for all IRES researchers, and can be used in other genomics applications such as gene annotation and analysis of differential gene expression.

Indexed as

Software5' Untranslated RegionsAlgorithmsBase SequenceComputational BiologyHumansInternal Ribosome Entry SitesModels, TheoreticalProbabilityRNA, Viral5' Untranslated RegionsInternal Ribosome Entry SitesRNA, ViralBioinformaticsInternal ribosome entry site (IRES)Machine learningXGBoost

Identifiers

PMID31362694
PMCPMC6664791
OpenAlexW2966361671

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.