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NetMe 2.0:一个基于网络的平台,用于从生物医学文献中提取和建模知识,作为标记图形

Antonio Di Maria¹, Lorenzo Bellomo², Fabrizio Billeci³

¹Department of Clinical and Experimental Medicine, University of Catania, Catania, 95125, Italy.

Bioinformatics (Oxford, England)

|April 10, 2024

概括

科学家现在可以使用NetMe 2.0.0.从文献中建立准确的生物医学网络. 这个平台提取实体和关系,创建知识图表并生成解释以更容易理解.

科学领域:

生物信息学是一种生物信息学.
计算生物学计算生物学
生物医学信息学生物医学信息学

背景情况:

生物医学文献的指数增长对寻求与科学进步保持最新状态的研究人员来说是一个重大挑战.
网络分析是生命科学中至关重要的计算工具,但从文献中构建准确和全面的生物医学网络仍然很困难.

研究的目的:

介绍NetMe 2.0,一个基于Web的平台,旨在自动构建生物医学知识图 (BKG) 从各种文本来源.
通过创新的检索增强生成 (Graph-RAG) 模块来增强BKG的实用性,用于生成解释性句子.

主要方法:

NetMe 2.0自动从用户提供的文本 (PubMed Central文章,自由文本,PDF) 中提取生物医学实体及其关系.
提取的信息被建模成一个生物医学知识图 (BKG).
一个Graph-RAG模块处理BKG以生成解释模拟关系的连贯句子.

主要成果:

网米2.0成功地推断出全面和可靠的生物网络.
与现有的最先进的方法相比,该平台展示了重要的精密召回指标.
图形-RAG模块有效地提炼了解释BKG内容的形成良好的句子.

结论:

从广泛的文献中,NetMe 2.0提供了一个强大的解决方案,以克服构建生物医学网络的挑战.
该平台通过自动化知识图表构建和解释生成,促进对复杂的生物关系的更深入的理解.
网米2.0可在https://netme.click/.上使用.

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