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发现和可视化生物医学概念之间的间接关联。

Discovering and visualizing indirect associations between biomedical concepts.

机构信息

School of Information Science, Japan Advanced Institute of Science and Technology (JAIST), Nomi, Japan.

出版信息

Bioinformatics. 2011 Jul 1;27(13):i111-9. doi: 10.1093/bioinformatics/btr214.

DOI:10.1093/bioinformatics/btr214
PMID:21685059
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3117364/
Abstract

MOTIVATION

Discovering useful associations between biomedical concepts has been one of the main goals in biomedical text-mining, and understanding their biomedical contexts is crucial in the discovery process. Hence, we need a text-mining system that helps users explore various types of (possibly hidden) associations in an easy and comprehensible manner.

RESULTS

This article describes FACTA+, a real-time text-mining system for finding and visualizing indirect associations between biomedical concepts from MEDLINE abstracts. The system can be used as a text search engine like PubMed with additional features to help users discover and visualize indirect associations between important biomedical concepts such as genes, diseases and chemical compounds. FACTA+ inherits all functionality from its predecessor, FACTA, and extends it by incorporating three new features: (i) detecting biomolecular events in text using a machine learning model, (ii) discovering hidden associations using co-occurrence statistics between concepts, and (iii) visualizing associations to improve the interpretability of the output. To the best of our knowledge, FACTA+ is the first real-time web application that offers the functionality of finding concepts involving biomolecular events and visualizing indirect associations of concepts with both their categories and importance.

AVAILABILITY

FACTA+ is available as a web application at http://refine1-nactem.mc.man.ac.uk/facta/, and its visualizer is available at http://refine1-nactem.mc.man.ac.uk/facta-visualizer/.

CONTACT

tsuruoka@jaist.ac.jp.

摘要

动机

发现生物医学概念之间的有用关联一直是生物医学文本挖掘的主要目标之一，理解它们的生物医学背景对于发现过程至关重要。因此，我们需要一个文本挖掘系统，帮助用户以简单易懂的方式探索各种类型的（可能隐藏的）关联。

结果

本文描述了 FACTA+，这是一个从 MEDLINE 摘要中发现和可视化生物医学概念之间间接关联的实时文本挖掘系统。该系统可以用作类似于 PubMed 的文本搜索引擎，并具有额外的功能，帮助用户发现和可视化重要生物医学概念（如基因、疾病和化学化合物）之间的间接关联。FACTA+继承了其前身 FACTA 的所有功能，并通过集成三个新功能进行了扩展：（i）使用机器学习模型检测文本中的生物分子事件，（ii）使用概念之间的共现统计数据发现隐藏关联，以及（iii）可视化关联以提高输出的可解释性。据我们所知，FACTA+是第一个提供发现涉及生物分子事件的概念并可视化概念与其类别和重要性的间接关联的实时网络应用程序。

可用性

FACTA+ 作为一个网络应用程序可在 http://refine1-nactem.mc.man.ac.uk/facta/ 上获得，其可视化工具可在 http://refine1-nactem.mc.man.ac.uk/facta-visualizer/ 上获得。

联系

tsuruoka@jaist.ac.jp。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b9d7/3117364/642b4a06d766/btr214f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b9d7/3117364/264989d49001/btr214f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b9d7/3117364/ae616d14c714/btr214f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b9d7/3117364/67a0ca53549e/btr214f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b9d7/3117364/642b4a06d766/btr214f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b9d7/3117364/264989d49001/btr214f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b9d7/3117364/ae616d14c714/btr214f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b9d7/3117364/67a0ca53549e/btr214f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b9d7/3117364/642b4a06d766/btr214f4.jpg

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