研究基因调控机制的数据集成方法

Jane Synnergren, B. Olsson, Jonas Gamalielsson
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引用次数: 1

摘要

系统生物学旨在了解活细胞的各种组成部分,如基因、蛋白质和代谢物之间的行为和相互作用。在这些复杂的系统中涉及大量的组件,并且组件之间的关系的多样性可能是压倒性的,因此需要包含数据集成的分析方法。我们在此提出了一种探索基因调控机制的方法,该方法整合了各种类型的数据,以帮助识别基因调控机制中的重要组成部分。首先分析基因表达数据,选择一组差异表达基因。然后,通过结合各种类型的生物学信息,如聚类结果、启动子序列、结合位点、转录因子和其他先前公布的有关所选基因的信息,对这些基因进行进一步研究。受信息融合研究的启发,我们还将该方法的功能映射到知名的ooda模型,以促进该数据集成方法在其他研究领域的应用。我们已经成功地将这种方法应用于在人类胚胎干细胞向心脏细胞分化的不同阶段被鉴定为差异表达的基因。我们确定了15个新的基序,它们可能代表心脏细胞谱系中重要的结合位点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A data integration method for exploring gene regulatory mechanisms
Systems biology aims to understand the behavior of and interaction between various components of the living cell, such as genes, proteins, and metabolites. A large number of components are involved in these complex systems and the diversity of relationships between the components can be overwhelming, and there is therefore a need for analysis methods incorporating data integration. We here present a method for exploring gene regulatory mechanisms which integrates various types of data to assist the identification of important components in gene regulation mechanisms. By first analyzing gene expression data, a set of differentially expressed genes is selected. These genes are then further investigated by combining various types of biological information, such as clustering results, promoter sequences, binding sites, transcription factors and other previously published information regarding the selected genes. Inspired by Information Fusion research, we also mapped functions of the proposed method to the well-known OODA-model to facilitate application of this data integration method in other research communities. We have successfully applied the method to genes identified as differentially expressed in human embryonic stem cells at different stages of differentiation towards cardiac cells. We identified 15 novel motifs that may represent important binding sites in the cardiac cell linage.
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