Inference of causal interaction networks of gut microbiota using transfer entropy
Abstract Background Understanding the complex dynamics of gut microbiota interactions is essential for unraveling their influence on human health. However, inferring causality from microbiome time-series data is challenging due to noise, sparsity, and high dimensionality. Constructing causal interac...
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| Главные авторы: | , , |
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| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
BMC
2025-12-01
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| Серии: | BMC Genomics |
| Предметы: | |
| Online-ссылка: | https://doi.org/10.1186/s12864-025-12384-1 |
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