Tools for the text mining-based visualisation of the provenance of biochemical networks

基于文本挖掘的生化网络起源可视化工具

• 批准号: BB/E004431/1
• 负责人: Sophia Ananiadou
• 金额: $ 70.01万
• 依托单位: University of Manchester
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2007
• 资助国家: 英国
• 起止时间: 2007 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FE004431%2F1
• 关键词: Tools; text; mining; based; visualisation

Systems biology is concerned with the modelling, visualisation and analysis of biochemical networks in which, for instance, metabolites are 'linked' by arrows representing the enzymes which turn one molecule into another or which are modified by particular substances. However, these diagrams are divorced from the scientific evidence on which they are based, which is represented by the scientific literature (and increasingly by online databases). However, the historical scientific literature is huge, and is increasing at an enormous rate (several thousand papers per week) so no one can possibly read it all. One solution is to use computers to 'read' these papers and present to the user only those which carry relevant information. Aspects of this subject are variously known as Natural Language Processing and Text Mining. What Text Mining does is to go through papers, extract the relevant pieces of information from each paper, and present them to the biological reader. A particular problem is the use by biologists of multiple names for the same thing. Text Mining can assist here since it is able to find all the variations of the same name and link them with the relevant text and databases. Text mining can also find the TYPES of relationship between these names, and this is the basis by which computers can discover and display scientific evidence. The Text Mining System will produce and index such evidence, for specific problems, and this will be stored in an appropriately structured database. The aim of the project is therefore to develop and deploy the necessary Text Mining tools and to use them to display the different relationships to the user and the literature on which they are based. This will be done by encoding the interactions using arrows of various colours that will link to a dynamic website of relevant literature that will thus give a direct linkage between the systems biology diagrams and the evidence for them.

系统生物学关注的是生化网络的建模、可视化和分析，例如，代谢物通过箭头“连接”，箭头代表将一个分子转化为另一个分子或被特定物质修饰的酶。然而，这些图表脱离了它们所基于的科学证据，这些科学证据由科学文献（以及越来越多的在线数据库）代表。然而，历史科学文献是巨大的，并以惊人的速度增加（每周数千篇论文），所以没有人可能阅读它。一种解决办法是用计算机“阅读”这些文件，并只向用户呈现那些携带相关信息的文件。这个主题的各个方面被称为自然语言处理和文本挖掘。文本挖掘所做的就是浏览论文，从每篇论文中提取相关的信息片段，并将其呈现给生物学读者。一个特别的问题是生物学家对同一事物使用多个名称。文本挖掘可以在这里提供帮助，因为它能够找到同名的所有变体并将它们与相关文本和数据库链接起来。文本挖掘还可以发现这些名称之间的关系类型，这是计算机发现和显示科学证据的基础。文本挖掘系统将为具体问题产生此类证据并编制索引，并将其存储在结构适当的数据库中。因此，该项目的目的是开发和部署必要的文本挖掘工具，并使用它们向用户和它们所基于的文献显示不同的关系。这将通过使用各种颜色的箭头对相互作用进行编码来完成，这些箭头将链接到相关文献的动态网站，从而在系统生物学图表和证据之间建立直接联系。

项目成果

Themes in biomedical natural language processing: BioNLP08.

• DOI: 10.1186/1471-2105-9-s11-s1
• 发表时间: 2008-11-19
• 期刊: BMC bioinformatics
• 影响因子: 3
• 作者: Demner-Fushman D;Ananiadou S;Cohen KB;Pestian J;Tsujii J;Webber B
• 通讯作者: Webber B

Building a high-quality sense inventory for improved abbreviation disambiguation.

• DOI: 10.1093/bioinformatics/btq129
• 发表时间: 2010-05-01
• 期刊: Bioinformatics (Oxford, England)
• 作者: Okazaki N;Ananiadou S;Tsujii J
• 通讯作者: Tsujii J

Automatic extraction of microorganisms and their habitats from free text using text mining workflows.

使用文本挖掘工作流程从自由文本中自动提取微生物及其栖息地。

• DOI: 10.2390/biecoll-jib-2011-184
• 发表时间: 2011
• 期刊: Journal of integrative bioinformatics
• 影响因子: 1.9
• 作者: Kolluru B

U-Compare: share and compare text mining tools with UIMA.

• DOI: 10.1093/bioinformatics/btp289
• 发表时间: 2009-08-01
• 期刊: Bioinformatics (Oxford, England)
• 作者: Kano Y;Baumgartner WA Jr;McCrohon L;Ananiadou S;Cohen KB;Hunter L;Tsujii J
• 通讯作者: Tsujii J

PathText: a text mining integrator for biological pathway visualizations.

• DOI: 10.1093/bioinformatics/btq221
• 发表时间: 2010-06-15
• 期刊: Bioinformatics (Oxford, England)
• 作者: Kemper B;Matsuzaki T;Matsuoka Y;Tsuruoka Y;Kitano H;Ananiadou S;Tsujii J
• 通讯作者: Tsujii J