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Comprehensive Analysis of Features and Annotations of Pathway Databases
Current Bioinformatics ( IF 4 ) Pub Date : 2020-09-30 , DOI: 10.2174/1574893615999200413123352
Ali Ghulam 1 , Xiujuan Lei 1 , Min Guo 1 , Chen Bian 1
Affiliation  

This study focused on describing the necessary information related to pathway mechanisms, characteristics, and databases feature annotations. Various difficulties related to data storage and retrieval in biological pathway databases are discussed. These focus on different techniques for retrieving annotations, features, and methods of digital pathway databases for biological pathway analysis. Furthermore, many pathway databases annotations, features, and search databases were also examined (which are reasonable for the integration into microarray examination). The investigation was performed on the databases, which contain human pathways to understand the hidden components of cells applied in this process. Three different domain-specific pathways were selected for this study and the information of pathway databases was extracted from the existing literature. The research compared different pathways and performed molecular level relations. Moreover, the associations between pathway networks were also evaluated. The study involved datasets for gene pathway matrices and pathway scoring techniques. Additionally, different pathways techniques, such as metabolomics and biochemical pathways, translation, control, and signaling pathways and signal transduction, were also considered. We also analyzed the list of gene sets and constructed a gene pathway network. This article will serve as a useful manual for storing a repository of specific biological data and disease pathways.



中文翻译:

路径数据库特征和注释的综合分析

这项研究的重点是描述与途径机制,特征和数据库特征注释有关的必要信息。讨论了与生物途径数据库中的数据存储和检索有关的各种困难。这些重点在于用于检索生物途径分析的数字途径数据库的注释,功能和方法的不同技术。此外,还检查了许多途径数据库的注释,特征和搜索数据库(对于整合到微阵列检查中是合理的)。该调查是在数据库中进行的,该数据库包含人类途径,以了解在此过程中应用的细胞的隐藏成分。为这项研究选择了三种不同的领域特异性途径,并且从现有文献中提取了途径数据库的信息。该研究比较了不同的途径并进行了分子水平的关系。此外,还评估了通路网络之间的关联。该研究涉及基因途径矩阵和途径评分技术的数据集。另外,还考虑了不同的途径技术,例如代谢组学和生化途径,翻译,控制和信号传导途径以及信号转导。我们还分析了基因集的列表,并构建了基因途径网络。本文将作为有用的手册,用于存储特定生物学数据和疾病途径的资料库。该研究比较了不同的途径并进行了分子水平的关系。此外,还评估了通路网络之间的关联。该研究涉及基因途径矩阵和途径评分技术的数据集。另外,还考虑了不同的途径技术,例如代谢组学和生化途径,翻译,控制和信号传导途径以及信号转导。我们还分析了基因集的列表,并构建了基因途径网络。本文将作为有用的手册,用于存储特定生物学数据和疾病途径的资料库。该研究比较了不同的途径并进行了分子水平的关系。此外,还评估了通路网络之间的关联。该研究涉及基因途径矩阵和途径评分技术的数据集。另外,还考虑了不同的途径技术,例如代谢组学和生化途径,翻译,控制和信号传导途径以及信号转导。我们还分析了基因集的列表,并构建了基因途径网络。本文将作为有用的手册,用于存储特定生物学数据和疾病途径的资料库。例如代谢组学和生化途径,翻译,控制,信号传导途径和信号转导等。我们还分析了基因集的列表,并构建了基因途径网络。本文将作为有用的手册,用于存储特定生物学数据和疾病途径的资料库。例如代谢组学和生化途径,翻译,控制,信号传导途径和信号转导等。我们还分析了基因集的列表,并构建了基因途径网络。本文将作为有用的手册,用于存储特定生物学数据和疾病途径的资料库。

更新日期:2020-09-30
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