Metabolite-disease interaction prediction based on logistic matrix factorization and local neighborhood constraints
Bibliographic Data
| ID | 15522880 |
|---|---|
| Authors | Yongbiao Zhao (0000-0002-4090-9185, Central China Normal University), Yuanyuan Ma (0000-0002-1090-4551, Hubei University of Arts and Science, corresponding author), Qilin Zhang (0000-0003-2687-5369, Hubei University of Arts and Science) |
| Year | 2023 |
| Volume | 14 |
| Pages | 1149947-1149947 |
| Publication date | 2023-06-05 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Frontiers in Psychiatry (JOURNAL) |
| Journal identifiers | ISSN: 1664-0640 • E-ISSN: 1664-0640 |
| Publisher | Frontiers Media (PUBLISHER • CH) |
| DOI | 10.3389/fpsyt.2023.1149947 |
| PMID | 37342171 |
| OpenAlex | W4379467780 |
| Language | EN |
| References cited | 21 |
The proposed LMFLNC method can well preserve the geometrical structure of original data and can thus effectively predict the underlying associations between metabolites and diseases. The experimental results show its effectiveness in metabolite-disease interaction prediction
Biology · Computational biology · Disease · Matrix decomposition · Metabolite · Non-negative matrix factorization · Physics · Similarity (geometry · Bioinformatics and Genomic Networks · Computer Science · Machine Learning in Bioinformatics · Medicine · Metabolomics and Mass Spectrometry Studies · Artificial Intelligence · Biochemistry · Internal Medicine
| Highly cited | No |
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