Discovering gene functional relationships using FAUN (Feature Annotation Using Nonnegative matrix factorization).
Discovering gene functional relationships using FAUN (Feature Annotation Using Nonnegative matrix factorization).
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DOI：
10.1186/1471-2105-11-s6-s14
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发表时间：
2010-10-07
影响因子：
3
通讯作者：
Homayouni R
中科院分区：
文献类型：
--
作者：
Tjioe E;Berry MW;Homayouni R
搜索生物医学文献中的大量可用信息以提取基因之间新的功能关系仍然是生物信息学领域的挑战。虽然已经开发了许多（软件）工具来从生物数据库中提取和识别基因关系，但很少有工具能够有效地处理提取新的（或隐含的）基因关系，而这一过程对于解释面向发现的全基因组实验很有用。在这项研究中，我们开发了一个基于网络的生物信息学软件环境，称为 FAUN 或使用非负矩阵分解 (NMF) 的特征注释，以促进基因之间功能关系的发现和分类。讨论了 NMF 用于处理基因集的计算复杂性和参数化。 FAUN 在三个手动构建的基因文档集合上进行了测试。它作为知识发现工具的实用性和性能是通过一组与自闭症相关的基因来证明的。 FAUN不仅帮助研究人员有效地利用生物医学文献，还为知识发现提供了实用工具。这种基于网络的软件环境可用于验证和分析高通量实验鉴定的基因子集中的功能关联。
Searching the enormous amount of information available in biomedical literature to extract novel functional relationships among genes remains a challenge in the field of bioinformatics. While numerous (software) tools have been developed to extract and identify gene relationships from biological databases, few effectively deal with extracting new (or implied) gene relationships, a process which is useful in interpretation of discovery-oriented genome-wide experiments. In this study, we develop a Web-based bioinformatics software environment called FAUN or Feature Annotation Using Nonnegative matrix factorization (NMF) to facilitate both the discovery and classification of functional relationships among genes. Both the computational complexity and parameterization of NMF for processing gene sets are discussed. FAUN is tested on three manually constructed gene document collections. Its utility and performance as a knowledge discovery tool is demonstrated using a set of genes associated with Autism. FAUN not only assists researchers to use biomedical literature efficiently, but also provides utilities for knowledge discovery. This Web-based software environment may be useful for the validation and analysis of functional associations in gene subsets identified by high-throughput experiments.