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GOAL：一个用于评估基因组合生物学意义的软件工具。

GOAL: a software tool for assessing biological significance of genes groups.

机构信息

Knowledge Discovery Group, Institute for Information Technology, National Research Council, Canada, 1200 Montreal Road, Ottawa, ON K1A 0R6 Canada.

出版信息

BMC Bioinformatics. 2010 May 6;11:229. doi: 10.1186/1471-2105-11-229.

DOI:10.1186/1471-2105-11-229
PMID:20459620
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2873542/
Abstract

BACKGROUND

Modern high throughput experimental techniques such as DNA microarrays often result in large lists of genes. Computational biology tools such as clustering are then used to group together genes based on their similarity in expression profiles. Genes in each group are probably functionally related. The functional relevance among the genes in each group is usually characterized by utilizing available biological knowledge in public databases such as Gene Ontology (GO), KEGG pathways, association between a transcription factor (TF) and its target genes, and/or gene networks.

RESULTS

We developed

GOAL

Gene Ontology AnaLyzer, a software tool specifically designed for the functional evaluation of gene groups. GOAL implements and supports efficient and statistically rigorous functional interpretations of gene groups through its integration with available GO, TF-gene association data, and association with KEGG pathways. In order to facilitate more specific functional characterization of a gene group, we implement three GO-tree search strategies rather than one as in most existing GO analysis tools. Furthermore, GOAL offers flexibility in deployment. It can be used as a standalone tool, a plug-in to other computational biology tools, or a web server application.

CONCLUSION

We developed a functional evaluation software tool, GOAL, to perform functional characterization of a gene group. GOAL offers three GO-tree search strategies and combines its strength in function integration, portability and visualization, and its flexibility in deployment. Furthermore, GOAL can be used to evaluate and compare gene groups as the output from computational biology tools such as clustering algorithms.

摘要

背景

现代高通量实验技术，如 DNA 微阵列，通常会产生大量基因列表。然后，使用计算生物学工具（如聚类）根据基因表达谱的相似性对基因进行分组。每个组中的基因可能具有功能相关性。通常利用公共数据库（如基因本体论（GO）、KEGG 途径、转录因子（TF）与其靶基因之间的关联以及/或基因网络）中的可用生物学知识来描述每个组中基因之间的功能相关性。

结果

我们开发了 GOAL：Gene Ontology AnaLyzer，这是一种专门为基因组功能评估而设计的软件工具。GOAL 通过与可用的 GO、TF-基因关联数据以及与 KEGG 途径的关联，实现并支持对基因组的有效和严格的统计功能解释。为了更具体地对基因组进行功能描述，我们实现了三种 GO 树搜索策略，而不是大多数现有 GO 分析工具中的一种。此外，GOAL 在部署方面具有灵活性。它可以作为独立工具、其他计算生物学工具的插件或 Web 服务器应用程序使用。

结论

我们开发了一种功能评估软件工具 GOAL，用于对基因组进行功能特征描述。GOAL 提供了三种 GO 树搜索策略，并结合了其在功能集成、可移植性和可视化方面的优势以及部署的灵活性。此外，GOAL 可用于评估和比较聚类算法等计算生物学工具的输出基因组。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6583/2873542/7d22a727268c/1471-2105-11-229-6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6583/2873542/9178e8438d41/1471-2105-11-229-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6583/2873542/2370a6629212/1471-2105-11-229-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6583/2873542/6f5693fd212a/1471-2105-11-229-3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6583/2873542/0bfac3839031/1471-2105-11-229-4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6583/2873542/3fe5647762d9/1471-2105-11-229-5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6583/2873542/7d22a727268c/1471-2105-11-229-6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6583/2873542/9178e8438d41/1471-2105-11-229-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6583/2873542/2370a6629212/1471-2105-11-229-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6583/2873542/6f5693fd212a/1471-2105-11-229-3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6583/2873542/0bfac3839031/1471-2105-11-229-4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6583/2873542/3fe5647762d9/1471-2105-11-229-5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6583/2873542/7d22a727268c/1471-2105-11-229-6.jpg

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