Evidence map›Paper›PMID 31267133›Full record

ArticleDatabase : the journal of biological databases and curation2019

piRDisease v1.0: a manually curated database for piRNA associated diseases.

Azhar Muhammad, Ramay Waheed, Nauman Ali Khan, Hong Jiang, Xiaoyuan Song

Open access · goldAbstract read
In one paragraph

Article in Database : the journal of biological databases and curation, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 1 pooled it
8.7field-weighted citation impact, top 3% 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

30 citing papers in PubMed, 1 synthesis or guideline pooled it, 56 citations in OpenAlex.

  1. Pooled it
  2. LLM4PDA: Augmenting piRNA-Disease Association Prediction with Large Language Models.Interdisciplinary sciences, computational life sciences · 2026
    Article
  3. Review
  4. Review
  5. Article
  6. Article
  7. Review
  8. Review
  9. Review
  10. piRNA associates with immune diseases.Cell communication and signaling : CCS · 2024
    Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Review
  20. Identification of piRNA disease associations using deep learning.Computational and structural biotechnology journal · 2022
    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

5 authors at 4 institutions in 2 countries.

Azhar MuhammadHefei National Laboratory for Physical Sciences at the Microscale, CAS Key Laboratory of Brain Function and Disease, Neurodegenerative Disorder Research Center, School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230026, China.
Ramay WaheedPattern Recognition and Information Retrieval lab, University of Science and Technology Beijing, Beijing 100083, China.
Nauman Ali KhanKey Laboratory of Wireless Optical Communication, Chinese Academy of Sciences, University of Science and Technology China, Hefei 230026, China.
Hong JiangHefei National Laboratory for Physical Sciences at the Microscale, CAS Key Laboratory of Brain Function and Disease, Neurodegenerative Disorder Research Center, School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230026, China.
Xiaoyuan SongHefei National Laboratory for Physical Sciences at the Microscale, CAS Key Laboratory of Brain Function and Disease, Neurodegenerative Disorder Research Center, School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230026, China.
University of Science and Technology of China · CNChinese Academy of Sciences · CNHefei National Center for Physical Sciences at Nanoscale · CNUniversity of Science and Technology Beijing · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent years, researches focusing on PIWI-interacting RNAs (piRNAs) have increased rapidly. It has been revealed that piRNAs have strong association with a wide range of diseases; thus, it becomes very important to understand piRNAs' role(s) in disease diagnosis, prognosis and assessment of treatment response. We searched more than 2500 articles using keywords, such as `PIWI-interacting RNAs' and `piRNAs', and further scrutinized the articles to collect piRNAs-disease association data. These data are highly complex and heterogeneous due to various types of piRNA idnetifiers (IDs) and different reference genome versions. We put considerable efforts into removing redundancy and anomalies and thus homogenized the data. Finally, we developed the piRDisease database, which incorporates experimentally supported data for piRNAs' relationship with wide range of diseases. The piRDisease (piRDisease v1.0) is a novel, comprehensive and exclusive database resource, which provides 7939 manually curated associations of experimentally supported 4796 piRNAs involved in 28 diseases. piRDisease facilitates users by providing detailed information of the piRNA in respective disease, explored by experimental support, brief description, sequence and location information. Considering piRNAs' role(s) in wide range of diseases, it is anticipated that huge amount of data would be produced in the near future. We thus offer a submitting page, on which users or researches can contribute in to update our piRDisease database.

Indexed as

Databases, Nucleic AcidData CurationRNA, Small InterferingDiseaseHumansRNA, Small Interfering

Identifiers

PMID31267133
PMCPMC6606758
OpenAlexW2955033696

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.