Evidence map›Paper›PMID 25165703›Full record

ArticleBioMed research international2014

Gene ontology and KEGG enrichment analyses of genes related to age-related macular degeneration.

Jian Zhang, ZhiHao Xing, Mingming Ma, Ning Wang, Yu-Dong Cai, Lei Chen, Xun Xu

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In one paragraph

Article in BioMed research international, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

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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

7 authors.

Jian ZhangDepartment of Ophthalmology, Shanghai First People's Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200080, China ; Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai First People's Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200080, China.
ZhiHao XingThe Key Laboratory of Stem Cell Biology, Institute of Health Sciences, Shanghai Jiaotong University School of Medicine and Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200025, China.
Mingming MaDepartment of Ophthalmology, Shanghai First People's Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200080, China ; Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai First People's Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200080, China.
Ning WangDepartment of Ophthalmology, Shanghai First People's Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200080, China ; Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai First People's Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200080, China.
Yu-Dong CaiInstitute of Systems Biology, Shanghai University, Shanghai 200444, China.
Lei ChenCollege of Information Engineering, Shanghai Maritime University, Shanghai 201306, China.
Xun XuDepartment of Ophthalmology, Shanghai First People's Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200080, China ; Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai First People's Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200080, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Identifying disease genes is one of the most important topics in biomedicine and may facilitate studies on the mechanisms underlying disease. Age-related macular degeneration (AMD) is a serious eye disease; it typically affects older adults and results in a loss of vision due to retina damage. In this study, we attempt to develop an effective method for distinguishing AMD-related genes. Gene ontology and KEGG enrichment analyses of known AMD-related genes were performed, and a classification system was established. In detail, each gene was encoded into a vector by extracting enrichment scores of the gene set, including it and its direct neighbors in STRING, and gene ontology terms or KEGG pathways. Then certain feature-selection methods, including minimum redundancy maximum relevance and incremental feature selection, were adopted to extract key features for the classification system. As a result, 720 GO terms and 11 KEGG pathways were deemed the most important factors for predicting AMD-related genes.

Indexed as

Databases, GeneticMetabolic Networks and PathwaysGene OntologyHumansMacular DegenerationModels, Theoretical

Identifiers

PMID25165703
PMCPMC4140130

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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.