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对益生菌新疗效的计算预测
Sadegh Sulaimany1, Kajal Farahmandi2, Aso Mafakheri3
1Social and Biological Network Analysis Laboratory (SBNA), Department of Computer Engineering, University of Kurdistan, Sanandaj, Iran. s.sulaimany@uok.ac.ir.
Scientific reports
|May 24, 2024
概括
链接预测准确地识别了潜在的益生菌与疾病的关系,揭示了益生菌的新治疗用途,如胃肠道问题上的Lactobacillus jensenii.
科学领域:
- 微生物学 微生物学
- 生物信息学是一种生物信息学.
- 网络科学 网络科学
背景情况:
- 益生菌是有益的微生物,对各种疾病具有治疗潜力.
- 链接预测在分析复杂的生物和医学网络方面已经被证明是有效的.
研究的目的:
- 将链接预测应用于益生菌疾病网络,以发现新的益生菌疾病关联.
- 在这种情况下,评估不同链接预测算法的性能.
主要方法:
- 使用Probio和ICD-10数据构建了益生菌和疾病的双部分图.
- 应用了共同邻居,雅卡尔系数和亚当/阿达尔链接预测算法.
- 使用曲线下的面积 (AUC) 和精度指标评估算法性能.
主要成果:
- 共同邻居算法实现了最高的性能,AUC为0.96和精度为0.6.6.
- 这表明,基本的链接预测方法可以正确识别大量潜在的益生菌与疾病的关系.
- 通过文献搜索的验证证实了前20个预测中的6个,突出了Lactobacillus jensenii和Lactobacillus acidophilus的特定益处.
结论:
- 链接预测是发现新的益生菌与疾病联系的可行方法.
- 共同邻居算法在这个领域表现出强大的预测能力.
- 建议进行进一步的研究和临床研究,以验证额外的预测关联,并探索先进的算法.
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