"Upstream Analysis": An Integrated Promoter-Pathway Analysis Approach to Causal Interpretation of Microarray Data.

Jeannette Koschmann, Anirban Bhar, Philip Stegmaier, Alexander E Kel, Edgar Wingender
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引用次数: 61

Abstract

A strategy is presented that allows a causal analysis of co-expressed genes, which may be subject to common regulatory influences. A state-of-the-art promoter analysis for potential transcription factor (TF) binding sites in combination with a knowledge-based analysis of the upstream pathway that control the activity of these TFs is shown to lead to hypothetical master regulators. This strategy was implemented as a workflow in a comprehensive bioinformatic software platform. We applied this workflow to gene sets that were identified by a novel triclustering algorithm in naphthalene-induced gene expression signatures of murine liver and lung tissue. As a result, tissue-specific master regulators were identified that are known to be linked with tumorigenic and apoptotic processes. To our knowledge, this is the first time that genes of expression triclusters were used to identify upstream regulators.

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“上游分析”:微阵列数据因果解释的综合启动子通路分析方法。
提出了一种策略,允许对可能受共同调控影响的共表达基因进行因果分析。对潜在转录因子(TF)结合位点的最新启动子分析,结合对控制这些TF活性的上游途径的基于知识的分析,显示出假设的主调控因子。该策略在综合生物信息学软件平台中作为工作流实施。我们将此工作流程应用于通过萘诱导的小鼠肝脏和肺组织的基因表达特征中的新型三聚类算法鉴定的基因集。结果,组织特异性主调控因子被确定,已知与致瘤性和凋亡过程有关。据我们所知,这是首次使用表达簇基因来鉴定上游调控因子。
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来源期刊
自引率
0.00%
发文量
0
审稿时长
11 weeks
期刊介绍: High-Throughput (formerly Microarrays, ISSN 2076-3905) is a multidisciplinary peer-reviewed scientific journal that provides an advanced forum for the publication of studies reporting high-dimensional approaches and developments in Life Sciences, Chemistry and related fields. Our aim is to encourage scientists to publish their experimental and theoretical results based on high-throughput techniques as well as computational and statistical tools for data analysis and interpretation. The full experimental or methodological details must be provided so that the results can be reproduced. There is no restriction on the length of the papers. High-Throughput invites submissions covering several topics, including, but not limited to: Microarrays, DNA Sequencing, RNA Sequencing, Protein Identification and Quantification, Cell-based Approaches, Omics Technologies, Imaging, Bioinformatics, Computational Biology/Chemistry, Statistics, Integrative Omics, Drug Discovery and Development, Microfluidics, Lab-on-a-chip, Data Mining, Databases, Multiplex Assays.
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