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探索性搜索分布式生物数据以回答复杂的生物医学问题。

Explorative search of distributed bio-data to answer complex biomedical questions.

出版信息

BMC Bioinformatics. 2014;15 Suppl 1(Suppl 1):S3. doi: 10.1186/1471-2105-15-S1-S3. Epub 2014 Jan 10.

Abstract

BACKGROUND

The huge amount of biomedical-molecular data increasingly produced is providing scientists with potentially valuable information. Yet, such data quantity makes difficult to find and extract those data that are most reliable and most related to the biomedical questions to be answered, which are increasingly complex and often involve many different biomedical-molecular aspects. Such questions can be addressed only by comprehensively searching and exploring different types of data, which frequently are ordered and provided by different data sources. Search Computing has been proposed for the management and integration of ranked results from heterogeneous search services. Here, we present its novel application to the explorative search of distributed biomedical-molecular data and the integration of the search results to answer complex biomedical questions.

RESULTS

A set of available bioinformatics search services has been modelled and registered in the Search Computing framework, and a Bioinformatics Search Computing application (Bio-SeCo) using such services has been created and made publicly available at http://www.bioinformatics.deib.polimi.it/bio-seco/seco/. It offers an integrated environment which eases search, exploration and ranking-aware combination of heterogeneous data provided by the available registered services, and supplies global results that can support answering complex multi-topic biomedical questions.

CONCLUSIONS

By using Bio-SeCo, scientists can explore the very large and very heterogeneous biomedical-molecular data available. They can easily make different explorative search attempts, inspect obtained results, select the most appropriate, expand or refine them and move forward and backward in the construction of a global complex biomedical query on multiple distributed sources that could eventually find the most relevant results. Thus, it provides an extremely useful automated support for exploratory integrated bio search, which is fundamental for Life Science data driven knowledge discovery.

摘要

背景

日益产生的大量生物医学分子数据为科学家提供了潜在的有价值的信息。然而,如此庞大的数据量使得难以找到和提取那些最可靠和最相关的生物医学问题的数据,这些问题变得越来越复杂,并且经常涉及许多不同的生物医学分子方面。这些问题只能通过全面搜索和探索不同类型的数据来解决,而这些数据通常由不同的数据源进行排序和提供。搜索计算已经被提出用于管理和整合来自异构搜索服务的排名结果。在这里,我们提出了它在探索性搜索分布式生物医学分子数据和整合搜索结果以回答复杂生物医学问题中的新应用。

结果

一组可用的生物信息学搜索服务已经在搜索计算框架中进行了建模和注册,并且使用这些服务创建了一个名为 Bioinformatics Search Computing 的应用程序(Bio-SeCo),并在 http://www.bioinformatics.deib.polimi.it/bio-seco/seco/ 上公开提供。它提供了一个集成的环境,简化了搜索、探索和对可用注册服务提供的异构数据进行排序感知的组合,并提供了全局结果,以支持回答复杂的多主题生物医学问题。

结论

通过使用 Bio-SeCo,科学家可以探索可用的大型且非常异构的生物医学分子数据。他们可以轻松地进行不同的探索性搜索尝试,检查获得的结果,选择最合适的结果,并对其进行扩展或细化,然后在对多个分布式源进行全局复杂生物医学查询的构建中向前和向后移动,最终找到最相关的结果。因此,它为探索性综合生物搜索提供了极其有用的自动化支持,这对于生命科学数据驱动的知识发现至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec39/4015759/eb88483c7d5e/1471-2105-15-S1-S3-1.jpg

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