Evolution mechanism of scientific topics using inheritance and variation features of knowledge genes: A case study in the hematopoietic stem-cell field

This study explores the key factors and internal driving forces of knowledge creation by constructing a research framework for the evolution of knowledge genes. The evolutionary mechanism of scientific topics is examined through the inheritance and variation characteristics of knowledge genes. Subject–predicate–object triples are used to identify knowledge gene topics, which are further categorised into four types based on their stability and variation features. A knowledge gene evolution path is then developed using content similarity and inheritance across adjacent time slices. Multidimensional feature analysis is applied to explore the inheritance and variation dynamics of these knowledge genes. A case study in the hematopoietic stem cells field, supported by literature validation and expert consultation, demonstrates the effectiveness of this method in enhancing the understanding of the knowledge innovation mechanism.

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Publication Details

Journal
Journal of Information Science
Published
2025-04-15
DOI
https://doi.org/10.1177/01655515251330617
Primary Topic
Biomedical Text Mining and Ontologies
Type
article
Field-Weighted Citation Impact
0.00
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article

Evolution mechanism of scientific topics using inheritance and variation features of knowledge genes: A case study in the hematopoietic stem-cell field

Liang Chen, Chao Wang, Ming Ma, Haiyun Xu et al.
Journal of Information Science
Biomedical Text Mining and Ontologies
article

Evolution mechanism of scientific topics using inheritance and variation features of knowledge genes: A case study in the hematopoietic stem-cell field

Liang Chen, Chao Wang, Ming Ma, Haiyun Xu, LO Mallasiy Muhayil Asir
article en

Abstract

This study explores the key factors and internal driving forces of knowledge creation by constructing a research framework for the evolution of knowledge genes. The evolutionary mechanism of scientific topics is examined through the inheritance and variation characteristics of knowledge genes. Subject–predicate–object triples are used to identify knowledge gene topics, which are further categorised into four types based on their stability and variation features. A knowledge gene evolution path is then developed using content similarity and inheritance across adjacent time slices. Multidimensional feature analysis is applied to explore the inheritance and variation dynamics of these knowledge genes. A case study in the hematopoietic stem cells field, supported by literature validation and expert consultation, demonstrates the effectiveness of this method in enhancing the understanding of the knowledge innovation mechanism.

Journal of Information Science
Shandong University of Technology (CN), Institute of Scientific and Technical Information of China (CN), King Khalid University (SA), Nanjing University (CN)
Openalex Percentile: Top 93%
Biomedical Text Mining and Ontologies
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Evolution mechanism of scientific topics using inheritance and variation features of knowledge genes: A case study in the hematopoietic stem-cell field — Liang Chen, Chao Wang, et al. · Journal of Information Science (2025) | TGRS Research Map | TGRS