A graph-based recovery and decomposition of Swanson's hypothesis using semantic predications.
A graph-based recovery and decomposition of Swanson's hypothesis using semantic predications.
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DOI：
10.1016/j.jbi.2012.09.004
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发表时间：
2013-04
影响因子：
4.5
通讯作者：
Rindflesch, Thomas C.
中科院分区：
文献类型：
--
作者：
Cameron, Delroy;Bodenreider, Olivier;Yalamanchili, Hima;Tu Danh;Vallabhaneni, Sreeram;Thirunarayan, Krishnaprasad;Sheth, Amit P.;Rindflesch, Thomas C.
关键词：
本文提出了一种半自动恢复和分解斯旺森雷诺综合征-鱼油假说的方法。该方法利用从生物医学文献中提取的断言的语义（称为语义预测），沿着结构化的背景知识和基于图形的算法，半自动地捕获最初由Swanson手动发现的信息关联。证明斯旺森的人工密集型技术可以进行半自动，铺平了道路，从科学文献的全自动语义为基础的假设生成。从生物医学文献中获得的语义预测允许构建标记有向图，其中包含来自文献的概念之间的各种关联。通过将这些关联聚合成信息丰富的子图，斯旺森最初阐述的一些相关细节已经被发现。然而，通过利用背景知识来弥合文献中的重要知识差距，已经开发出一种用于半自动捕获Swanson最初用自然语言解释的详细关联的方法。我们的方法不仅恢复了3协会普遍公认的斯旺森的假设，但也分解成一个额外的16个详细的协会，制定为链的语义谓词。总之，14的19个协会，可以归因于斯旺森检索使用我们的方法。据我们所知，这样一个深入的恢复和分解斯旺森的假设从来没有尝试过。因此，在这项工作中，我们提出了一种方法，半自动恢复和分解斯旺森的RS-DFO假设使用语义表示和图形算法。我们的方法为语义驱动的基于文献的发现（LBD）的潜在先决条件提供了新的见解。这表明LBD的三个关键方面包括：1）需要比Swanson的ABC模型更有表现力的表示; 2）从文本中准确提取语义信息的能力; 3）科学文献与结构化背景知识的语义整合。
This paper presents a methodology for recovering and decomposing Swanson’s Raynaud Syndrome–Fish Oil Hypothesis semi-automatically. The methodology leverages the semantics of assertions extracted from biomedical literature (called semantic predications) along with structured background knowledge and graph-based algorithms to semi-automatically capture the informative associations originally discovered manually by Swanson. Demonstrating that Swanson’s manually intensive techniques can be undertaken semi-automatically, paves the way for fully automatic semantics-based hypothesis generation from scientific literature. Semantic predications obtained from biomedical literature allow the construction of labeled directed graphs which contain various associations among concepts from the literature. By aggregating such associations into informative subgraphs, some of the relevant details originally articulated by Swanson has been uncovered. However, by leveraging background knowledge to bridge important knowledge gaps in the literature, a methodology for semi-automatically capturing the detailed associations originally explicated in natural language by Swanson has been developed. Our methodology not only recovered the 3 associations commonly recognized as Swanson’s Hypothesis, but also decomposed them into an additional 16 detailed associations, formulated as chains of semantic predications. Altogether, 14 out of the 19 associations that can be attributed to Swanson were retrieved using our approach. To the best of our knowledge, such an in-depth recovery and decomposition of Swanson’s Hypothesis has never been attempted. In this work therefore, we presented a methodology for semi- automatically recovering and decomposing Swanson’s RS-DFO Hypothesis using semantic representations and graph algorithms. Our methodology provides new insights into potential prerequisites for semantics-driven Literature-Based Discovery (LBD). These suggest that three critical aspects of LBD include: 1) the need for more expressive representations beyond Swanson’s ABC model; 2) an ability to accurately extract semantic information from text; and 3) the semantic integration of scientific literature with structured background knowledge.
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DOI：
10.1109/bibm.2011.23
发表时间：
2011
期刊：
IEEE International Conference on Bioinformatics and Biomedicine workshops. IEEE International Conference on Bioinformatics and Biomedicine
影响因子：
--
作者：
Cameron D;Kavuluru R;Bodenreider O;Mendes PN;Sheth AP;Thirunarayan K
通讯作者：
Thirunarayan K
影响因子：
9.9
作者：
Smalheiser, NR;Swanson, DR
通讯作者：
Swanson, DR
影响因子：
8.3
作者：
MONCADA, S
通讯作者：
MONCADA, S
DOI：
10.1002/asi.21599
发表时间：
2012-02-01
影响因子：
--
作者：
Smalheiser, Neil R.
通讯作者：
Smalheiser, Neil R.
DOI：
10.1016/j.ijmedinf.2004.04.024
发表时间：
2005-03-01
影响因子：
4.9
作者：
Hristovski, D;Peterlin, B;Humphrey, SM
通讯作者：
Humphrey, SM