Preliminary exploration of multi-omics data fusion methods for high-dimensional small-sample datasets in traditional Chinese medicine.
10.19540/j.cnki.cjcmm.20241005.601
- Author:
Nian WANG
1
;
Cheng-Cheng YU
1
;
Hu YANG
2
;
Zhong WANG
1
;
Jun LIU
1
Author Information
1. Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences Beijing 100700, China.
2. School of Information, Central University of Finance and Economics Beijing 100081, China.
- Publication Type:Journal Article
- Keywords:
data fusion;
high-dimensional small-sample;
multi-omics;
traditional Chinese medicine
- MeSH:
Medicine, Chinese Traditional/methods*;
Humans;
Computational Biology/methods*;
Genomics/methods*;
Sample Size;
Artificial Intelligence;
Multiomics
- From:
China Journal of Chinese Materia Medica
2025;50(1):278-284
- CountryChina
- Language:Chinese
-
Abstract:
With the advancement in big data and artificial intelligence technologies, the extensive application of omics technologies in traditional Chinese medicine(TCM) research has generated large experimental datasets, enabling the exploration of cross-scale correlations among massive data and thereby resulting in the shift toward a data-intensive research paradigm. The emerging approach of multi-omics data fusion analysis, emphasizing technical and computational tools, presents a potential breakthrough in this field. The holistic perspective of TCM aligns with the concept of multi-omics data fusion, yet the data types encountered exhibit high dimensionality with small sample sizes, necessitating data processing techniques such as dimensionality reduction. The current challenge lies in selecting suitable analytical methods for these data to enhance the systematic understanding of physiological functions and disease diagnosis/treatment processes. This paper explores the theories and frameworks of multi-omics data fusion, analyzes methods for fusing high-dimensional, small-sample multi-omics data in TCM, and aims to provide insights for advancing TCM research.
