Literature DB >> 26471719

MeSHSim: An R/Bioconductor package for measuring semantic similarity over MeSH headings and MEDLINE documents.

Jing Zhou1,2, Yuxuan Shui1,2, Shengwen Peng1,2, Xuhui Li3, Hiroshi Mamitsuka4, Shanfeng Zhu1,2.   

Abstract

Currently, all MEDLINE documents are indexed by medical subject headings (MeSH). Computing semantic similarity between two MeSH headings as well as two documents has become very important for many biomedical text mining applications. We develop an R package, MeSHSim, which can compute nine similarity measures between MeSH nodes, by which similarity between MeSH headings as well as MEDLINE documents can be easily computed. Also, MeSHSim supports querying hierarchy information of a MeSH heading and retrieving MeSH headings of a query document, and can be easily integrated into pipelines for any biomedical text analysis tasks. MeSHSim is released under general public license (GPL), and available through Bioconductor and from Github at https://github.com/JingZhou2015/MeSHSim.

Keywords:  MEDLINE documents; MeSH; R/bioconductor package; semantic similarity

Mesh:

Year:  2015        PMID: 26471719     DOI: 10.1142/S0219720015420020

Source DB:  PubMed          Journal:  J Bioinform Comput Biol        ISSN: 0219-7200            Impact factor:   1.122


  10 in total

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Authors:  Stephen J Capuzzi; Thomas E Thornton; Kammy Liu; Nancy Baker; Wai In Lam; Colin P O'Banion; Eugene N Muratov; Diane Pozefsky; Alexander Tropsha
Journal:  J Chem Inf Model       Date:  2018-01-19       Impact factor: 4.956

2.  Gaps within the Biomedical Literature: Initial Characterization and Assessment of Strategies for Discovery.

Authors:  Yufang Peng; Gary Bonifield; Neil R Smalheiser
Journal:  Front Res Metr Anal       Date:  2017-05-22

3.  pyMeSHSim: an integrative python package for biomedical named entity recognition, normalization, and comparison of MeSH terms.

Authors:  Zhi-Hui Luo; Meng-Wei Shi; Zhuang Yang; Hong-Yu Zhang; Zhen-Xia Chen
Journal:  BMC Bioinformatics       Date:  2020-06-18       Impact factor: 3.169

4.  An Efficient Parallelized Ontology Network-Based Semantic Similarity Measure for Big Biomedical Document Clustering.

Authors:  Meijing Li; Tianjie Chen; Keun Ho Ryu; Cheng Hao Jin
Journal:  Comput Math Methods Med       Date:  2021-11-09       Impact factor: 2.238

5.  Automated Recommendation of Research Keywords from PubMed That Suggest the Molecular Mechanism Associated with Biomarker Metabolites.

Authors:  Shinji Kanazawa; Satoshi Shimizu; Shigeki Kajihara; Norio Mukai; Junko Iida; Fumio Matsuda
Journal:  Metabolites       Date:  2022-02-01

6.  An Ensemble Semantic Textual Similarity Measure Based on Multiple Evidences for Biomedical Documents.

Authors:  Meijing Li; Xianhe Zhou; Keun Ho Ryu; Nipon Theera-Umpon
Journal:  Comput Math Methods Med       Date:  2022-08-27       Impact factor: 2.809

7.  Two Similarity Metrics for Medical Subject Headings (MeSH): An Aid to Biomedical Text Mining and Author Name Disambiguation.

Authors:  Neil R Smalheiser; Gary Bonifield
Journal:  J Biomed Discov Collab       Date:  2016-04-06

8.  MeSH-Informed Enrichment Analysis and MeSH-Guided Semantic Similarity Among Functional Terms and Gene Products in Chicken.

Authors:  Gota Morota; Timothy M Beissinger; Francisco Peñagaricano
Journal:  G3 (Bethesda)       Date:  2016-08-09       Impact factor: 3.154

9.  Drug repurposing for cancer treatment through global propagation with a greedy algorithm in a multilayer network.

Authors:  Xi Cheng; Wensi Zhao; Mengdi Zhu; Bo Wang; Xuege Wang; Xiaoyun Yang; Yuqi Huang; Minjia Tan; Jing Li
Journal:  Cancer Biol Med       Date:  2021-04-24       Impact factor: 4.248

10.  MCRWR: a new method to measure the similarity of documents based on semantic network.

Authors:  Xianwei Pan; Peng Huang; Shan Li; Lei Cui
Journal:  BMC Bioinformatics       Date:  2022-02-01       Impact factor: 3.169

  10 in total

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