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GeneTrailExpress:一个用于微阵列实验统计评估的基于网络的流程

GeneTrailExpress: a web-based pipeline for the statistical evaluation of microarray experiments.

作者信息

Keller Andreas, Backes Christina, Al-Awadhi Maher, Gerasch Andreas, Küntzer Jan, Kohlbacher Oliver, Kaufmann Michael, Lenhof Hans-Peter

机构信息

Center for Bioinformatics, Saarland University, Saarbrücken, Germany.

出版信息

BMC Bioinformatics. 2008 Dec 22;9:552. doi: 10.1186/1471-2105-9-552.

DOI:10.1186/1471-2105-9-552
PMID:19099609
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2627893/
Abstract

BACKGROUND

High-throughput methods that allow for measuring the expression of thousands of genes or proteins simultaneously have opened new avenues for studying biochemical processes. While the noisiness of the data necessitates an extensive pre-processing of the raw data, the high dimensionality requires effective statistical analysis methods that facilitate the identification of crucial biological features and relations. For these reasons, the evaluation and interpretation of expression data is a complex, labor-intensive multi-step process. While a variety of tools for normalizing, analysing, or visualizing expression profiles has been developed in the last years, most of these tools offer only functionality for accomplishing certain steps of the evaluation pipeline.

RESULTS

Here, we present a web-based toolbox that provides rich functionality for all steps of the evaluation pipeline. Our tool GeneTrailExpress offers besides standard normalization procedures powerful statistical analysis methods for studying a large variety of biological categories and pathways. Furthermore, an integrated graph visualization tool, BiNA, enables the user to draw the relevant biological pathways applying cutting-edge graph-layout algorithms.

CONCLUSION

Our gene expression toolbox with its interactive visualization of the pathways and the expression values projected onto the nodes will simplify the analysis and interpretation of biochemical pathways considerably.

摘要

背景

能够同时测量数千个基因或蛋白质表达的高通量方法为研究生化过程开辟了新途径。虽然数据的噪声需要对原始数据进行广泛的预处理,但高维度需要有效的统计分析方法,以促进关键生物学特征和关系的识别。由于这些原因,表达数据的评估和解释是一个复杂、劳动密集型的多步骤过程。尽管在过去几年中已经开发了各种用于标准化、分析或可视化表达谱的工具,但这些工具大多仅提供完成评估流程某些步骤的功能。

结果

在此,我们展示了一个基于网络的工具箱,它为评估流程的所有步骤提供了丰富的功能。我们的工具GeneTrailExpress除了标准的标准化程序外,还提供强大的统计分析方法,用于研究各种生物学类别和途径。此外,一个集成的图形可视化工具BiNA,使用户能够应用前沿的图形布局算法绘制相关的生物学途径。

结论

我们的基因表达工具箱及其对途径的交互式可视化以及投影到节点上的表达值将大大简化生化途径的分析和解释。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9271/2627893/5d3018024ad1/1471-2105-9-552-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9271/2627893/36630e8ceb83/1471-2105-9-552-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9271/2627893/5d3018024ad1/1471-2105-9-552-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9271/2627893/36630e8ceb83/1471-2105-9-552-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9271/2627893/5d3018024ad1/1471-2105-9-552-2.jpg

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