Dataset Information

COEXPEDIA: exploring biomedical hypotheses via co-expressions associated with medical subject headings (MeSH).

ABSTRACT: The use of high-throughput array and sequencing technologies has produced unprecedented amounts of gene expression data in central public depositories, including the Gene Expression Omnibus (GEO). The immense amount of expression data in GEO provides both vast research opportunities and data analysis challenges. Co-expression analysis of high-dimensional expression data has proven effective for the study of gene functions, and several co-expression databases have been developed. Here, we present a new co-expression database, COEXPEDIA (www.coexpedia.org), which is distinctive from other co-expression databases in three aspects: (i) it contains only co-functional co-expressions that passed a rigorous statistical assessment for functional association, (ii) the co-expressions were inferred from individual studies, each of which was designed to investigate gene functions with respect to a particular biomedical context such as a disease and (iii) the co-expressions are associated with medical subject headings (MeSH) that provide biomedical information for anatomical, disease, and chemical relevance. COEXPEDIA currently contains approximately eight million co-expressions inferred from 384 and 248 GEO series for humans and mice, respectively. We describe how these MeSH-associated co-expressions enable the identification of diseases and drugs previously unknown to be related to a gene or a gene group of interest.

SUBMITTER: Yang S

PROVIDER: S-EPMC5210615 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature

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COEXPEDIA: exploring biomedical hypotheses via co-expressions associated with medical subject headings (MeSH).

Yang Sunmo S Kim Chan Yeong CY Hwang Sohyun S Kim Eiru E Kim Hyojin H Shim Hongseok H Lee Insuk I

Nucleic acids research 20160926 D1

The use of high-throughput array and sequencing technologies has produced unprecedented amounts of gene expression data in central public depositories, including the Gene Expression Omnibus (GEO). The immense amount of expression data in GEO provides both vast research opportunities and data analysis challenges. Co-expression analysis of high-dimensional expression data has proven effective for the study of gene functions, and several co-expression databases have been developed. Here, we present ...[more]

PMID: 27679477

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Project description:BackgroundMedical Subject Headings (MeSH) thesaurus contribute towards efficient searching of biomedical information. However, insufficient coverage of specific fields and inaccuracies in the indexing of articles can lead to bias during literature retrieval.ObjectivesThis meta-research study aimed to assess the use of 'Pharmaceutical Services' MeSH terms in studies evaluating the effect of pharmacists' interventions.MethodsAn updated systematic search (Jan-2022) to gather meta-analyses comparing pharmacists' interventions vs. other forms of care was performed. All MeSH terms allocated to the MEDLINE record of each primary study included in the selected meta-analyses were systematically extracted. Terms from the 'Pharmaceutical Services' branch, including its descendants, as well as other 26 pharmacy-specific MeSH terms were identified. The assignment of these terms as a 'Major MeSH' was also evaluated. Descriptive statistics and social network analyses to evaluate the co-occurrence of the MeSH terms in the articles were conducted. Sensitivity analyses including only meta-analyses with declared objectives mentioning the words 'pharmacist' or 'pharmacy' were performed (SPSS v.24.0).ResultsOverall, 138 meta-analyses including 2012 primary articles were evaluated. A median of 15 [IQR 12-18] MeSH terms were assigned per article with a slight positive time-trend (Spearman rho = 0.193; p < 0.001). Only 36.6% (n = 736/2012) and 58.1% (n = 338/1099) of studies were indexed with one MeSH term from the 'Pharmaceutical Services' branch in the overall and sensitivity analyses, respectively. In <20% of cases, these terms were a 'Major MeSH'. The pharmacy-specific term 'Pharmacists' was the most frequently used, yet in only 27.8% and 47.7% of articles in the original and sensitivity analyses, respectively. Social networks showed a weak association between pharmacy-specific and 'Pharmaceutical services' branch MeSH terms.ConclusionsThe availability of a 'Pharmaceutical services' branch hierarchic tree and further pharmacy-specific MeSH terms incorporated to the MeSH thesaurus in the past years is not related with accurate indexing of articles.

Dataset Information

COEXPEDIA: exploring biomedical hypotheses via co-expressions associated with medical subject headings (MeSH).

Publications

COEXPEDIA: exploring biomedical hypotheses via co-expressions associated with medical subject headings (MeSH).

Similar Datasets

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