Evidence map›Paper›PMID 25972728›Full record

ArticleCancer informatics2014

Pathway-based Biomarkers for Breast Cancer in Proteomics.

Fan Zhang, Youping Deng, Mu Wang, Li Cui, Renee Drabier

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cancer informatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Functional Genomics, Genetics, and Bioinformatics 2016.BioMed research international · 2016
    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.

Fan ZhangDepartment of Academic and Institutional Resources and Technology, University of North Texas Health Science Center, Fort Worth, TX, USA. ; Department of Forensic and Investigative Genetics, University of North Texas Health Science Center, Fort Worth, TX, USA.
Youping DengDepartment of Internal Medicine, Rush University Medical Center, Chicago, IL, USA.
Mu WangDepartment of Biochemistry and Molecular Biology, IU School of Medicine, Indianapolis, IN, USA. ; Indiana Center for Systems Biology and Personalized Medicine, Indianapolis, IN, USA.
Li CuiDepartment of Neurosciences, School of Medicine, University of San Diego, La Jolla, CA, USA.
Renee DrabierDepartment of Academic and Institutional Resources and Technology, University of North Texas Health Science Center, Fort Worth, TX, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genes do not function alone but through complex biological pathways. Pathway-based biomarkers may be a reliable diagnostic tool for early detection of breast cancer due to the fact that breast cancer is not a single homogeneous disease. We applied Integrated Pathway Analysis Database (IPAD) and Gene Set Enrichment Analysis (GSEA) approaches to the study of pathway-based biomarker discovery problem in breast cancer proteomics. Our strategy for identifying and analyzing pathway-based biomarkers are threefold. Firstly, we performed pathway analysis with IPAD to build the gene set database. Secondly, we ran GSEA to identify 16 pathway-based biomarkers. Lastly, we built a Support Vector Machine model with three-way data split and fivefold cross-validation to validate the biomarkers. The approach-unraveling the intricate pathways, networks, and functional contexts in which genes or proteins function-is essential to the understanding molecular mechanisms of pathway-based biomarkers in breast cancer.

Indexed as

breast cancermachine learningpathway analysisproteomics

Identifiers

PMID25972728
PMCPMC4324474

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.