Maracaja-Coutinho Vinicius, Paschoal Alexandre Rossi, Caris-Maldonado José Carlos, Borges Pedro Vinícius, Ferreira Almir José, Durham Alan Mitchell
Advanced Center for Chronic Diseases-ACCDiS, Facultad de Ciencias Químicas y Farmacéuticas, Universidad de Chile, Santiago, Chile.
Department of Computer Science, Bioinformatics Graduation Program (PPGBIOINFO), Federal University of Technology - Paraná, Cornélio Procópio, Brazil.
Methods Mol Biol. 2019;1912:251-285. doi: 10.1007/978-1-4939-8982-9_10.
One of the most important resources for researchers of noncoding RNAs is the information available in public databases spread over the internet. However, the effective exploration of this data can represent a daunting task, given the large amount of databases available and the variety of stored data. This chapter describes a classification of databases based on information source, type of RNA, source organisms, data formats, and the mechanisms for information retrieval, detailing the relevance of each of these classifications and its usability by researchers. This classification is used to update a 2012 review, indexing now more than 229 public databases. This review will include an assessment of the new trends for ncRNA research based on the information that is being offered by the databases. Additionally, we will expand the previous analysis focusing on the usability and application of these databases in pathogen and disease research. Finally, this chapter will analyze how currently available database schemas can help the development of new and improved web resources.
对于非编码RNA研究人员而言，最重要的资源之一是互联网上众多公共数据库中所提供的信息。然而，鉴于可用数据库数量庞大且存储的数据种类繁多，有效挖掘这些数据可能是一项艰巨的任务。本章基于信息来源、RNA类型、源生物体、数据格式以及信息检索机制对数据库进行了分类，详细阐述了每种分类的相关性以及研究人员对其的可用性。此分类用于更新2012年的一篇综述，目前索引了超过229个公共数据库。本综述将基于数据库提供的信息评估非编码RNA研究的新趋势。此外，我们将扩展先前的分析，重点关注这些数据库在病原体和疾病研究中的可用性及应用。最后，本章将分析当前可用的数据库模式如何助力新的、更完善的网络资源的开发。
