Evidence map›Paper›PMID 25462153›Full record

ReviewGenomics, proteomics & bioinformatics2014

Pathway-based analysis tools for complex diseases: a review.

Lv Jin, Xiao-Yu Zuo, Wei-Yang Su, Xiao-Lei Zhao, Man-Qiong Yuan, Li-Zhen Han, Xiang Zhao, Ye-Da Chen, Shao-Qi Rao

Abstract readReview
In one paragraph

Review in Genomics, proteomics & bioinformatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 74 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
74citing papers in PubMed, 1 pooled it
–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

74 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. The impact for causal associations between common diseases and inflammatory bowel disease: a disease-wide bidirectional Mendelian randomization study.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2026
    Article
  4. Review
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. PathIN: an integrated tool for the visualization of pathway interaction networks.Computational and structural biotechnology journal · 2023
    Article
  17. Article
  18. Article
  19. Article
  20. Article

14 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

9 authors.

Lv JinInstitute for Medical Systems Biology, and Department of Medical Statistics and Epidemiology, School of Public Health, Guangdong Medical College, Dongguan 523808, China.
Xiao-Yu ZuoDepartment of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-Sen University, Guangzhou 510080, China.
Wei-Yang SuCommunity Health Service Management Center of Panyu District, Guangzhou 511400, China.
Xiao-Lei ZhaoInstitute for Medical Systems Biology, and Department of Medical Statistics and Epidemiology, School of Public Health, Guangdong Medical College, Dongguan 523808, China.
Man-Qiong YuanDepartment of Statistical Sciences, School of Mathematics and Computational Science, Sun Yat-Sen University, Guangzhou 510275, China.
Li-Zhen HanDepartment of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-Sen University, Guangzhou 510080, China.
Xiang ZhaoInstitute for Medical Systems Biology, and Department of Medical Statistics and Epidemiology, School of Public Health, Guangdong Medical College, Dongguan 523808, China.
Ye-Da ChenInstitute for Medical Systems Biology, and Department of Medical Statistics and Epidemiology, School of Public Health, Guangdong Medical College, Dongguan 523808, China.
Shao-Qi RaoInstitute for Medical Systems Biology, and Department of Medical Statistics and Epidemiology, School of Public Health, Guangdong Medical College, Dongguan 523808, China; Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-Sen University, Guangzhou 510080, China; Department of Statistical Sciences, School of Mathematics and Computational Science, Sun Yat-Sen University, Guangzhou 510275, China. Electronic address: raoshaoq@gdmc.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genetic studies are traditionally based on single-gene analysis. The use of these analyses can pose tremendous challenges for elucidating complicated genetic interplays involved in complex human diseases. Modern pathway-based analysis provides a technique, which allows a comprehensive understanding of the molecular mechanisms underlying complex diseases. Extensive studies utilizing the methods and applications for pathway-based analysis have significantly advanced our capacity to explore large-scale omics data, which has rapidly accumulated in biomedical fields. This article is a comprehensive review of the pathway-based analysis methods-the powerful methods with the potential to uncover the biological depths of the complex diseases. The general concepts and procedures for the pathway-based analysis methods are introduced and then, a comprehensive review of the major approaches for this analysis is presented. In addition, a list of available pathway-based analysis software and databases is provided. Finally, future directions and challenges for the methodological development and applications of pathway-based analysis techniques are discussed. This review will provide a useful guide to dissect complex diseases.

Indexed as

Databases, FactualGene Regulatory NetworksSignal TransductionDiseaseHumansSoftwareAlgorithmsComplex diseasePathway-based analysisSoftware and databases

Identifiers

PMID25462153
PMCPMC4411419

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.