Dynamic Categorization of Biomedical Search Results

Because the number of biomedical publications is rising quickly, it becomes difficult to efficientlyobtain the needed information for major biology research by using repositories such as MEDLINE, EntrezGene and OMIM. Using traditional PubMed–like search tools often makes users deal with too muchinformation at once. As a result, users have to keep tweaking their searches, possibly overlookingimportant studies and it can get tiring mentally. BioNav is now used to group search results by using thedetailed Medical Subject Headings (MeSH) ontology as a tree structure. Browsing in this way is madeeasy by each node in the tree being a MeSH concept, helping users explore generic to particular subjects,as can be done when navigating product categories on e-commerce sites. When using BioNav, citations arematched to relevant concepts through MeSH tags and through detecting terms in the text and the nodes arearranged by how often the citations appear and their relevance. Because of this strategy, researchers find itis easier to locate studies about prothymosin in different fields of biomedical research.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-06-15
DOI
https://doi.org/10.5281/zenodo.15669406
Primary Topic
Biomedical Text Mining and Ontologies
Type
article
Field-Weighted Citation Impact
0.00
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article

Dynamic Categorization of Biomedical Search Results

Zenodo (CERN European Organization for Nuclear Research)
Biomedical Text Mining and Ontologies
article

Dynamic Categorization of Biomedical Search Results

article en

Abstract

Because the number of biomedical publications is rising quickly, it becomes difficult to efficientlyobtain the needed information for major biology research by using repositories such as MEDLINE, EntrezGene and OMIM. Using traditional PubMed–like search tools often makes users deal with too muchinformation at once. As a result, users have to keep tweaking their searches, possibly overlookingimportant studies and it can get tiring mentally. BioNav is now used to group search results by using thedetailed Medical Subject Headings (MeSH) ontology as a tree structure. Browsing in this way is madeeasy by each node in the tree being a MeSH concept, helping users explore generic to particular subjects,as can be done when navigating product categories on e-commerce sites. When using BioNav, citations arematched to relevant concepts through MeSH tags and through detecting terms in the text and the nodes arearranged by how often the citations appear and their relevance. Because of this strategy, researchers find itis easier to locate studies about prothymosin in different fields of biomedical research.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 60%
Biomedical Text Mining and Ontologies
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Dynamic Categorization of Biomedical Search Results · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS