Molecular biological databases: evolutionary history, data modeling, implementation and ethical background

M. Cooray
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引用次数: 3

Abstract

Influence from the rapidly growing fields of computer and information sciences in early 1970s was one of the major factors leading to the development of computer based repositories for biological data. Since the emergence of the first ever computer based molecular biological database ‘Protein Data Bank’ in 1971, biological database domain has grown rapidly in the areas of information content and volume, database modeling, implementation and integration. Key driving forces of this growth are: the amount and diversity of data generated from advancing biological research technologies, the challenges imposed on data modeling by the inherent properties of biological data and the concept of  ‘Electronic Data Publishing’ introduced in early 1990s. According to the database release of ‘Nucleic Acid Research’ in 2010, biological database number increased in about 5% during the year of 2009-2010 and in major databases like ‘GenBank’ data volume doubles approximately every 18 months. Due to the data modeling challenges driven by inherent properties of biological data, multiple modeling tools such as ‘Enhanced Entity Relationship’ diagrams and ‘Unified Modeling Language’ are used to model biological mini worlds. To be compatible with diverse data models, multiple implementation approaches are also used by the biological database developers, namely ‘Flat files’ , ‘XML’ , ‘Relational databases’ , ‘Object oriented databases’ , ‘ASN.1’ and etc. Adherence to simplicity and conservative technology provides a better practical approach to biological database modeling and implementation. Even though the biological databases differ in their internal data model, implementation approach and biological scope, almost all of them share similar 3 tier web architecture. This similarity is the basis of the current three major strategies used for database integration namely ‘Link/hypertext integration’ , ‘View integration’ and ‘Data warehousing’ . Ethical framework governing the molecular biological research and databases, need to be re-engineered to accommodate the demands imposed by this rapidly growing scientific field. Sri Lanka Journal of Bio-Medical informatics 2012; 3 (1):2-11 DOI: http://dx.doi.org/10.4038/sljbmi.v3i1.2489
分子生物学数据库:进化史、数据建模、实现和伦理背景
20世纪70年代初,计算机和信息科学领域的迅速发展是导致基于计算机的生物数据存储库发展的主要因素之一。自1971年第一个基于计算机的分子生物学数据库“蛋白质数据库”出现以来,生物数据库领域在信息内容和信息量、数据库建模、实现和集成等方面发展迅速。这种增长的主要驱动力是:先进的生物研究技术产生的数据的数量和多样性,生物数据的固有属性给数据建模带来的挑战,以及20世纪90年代初引入的“电子数据出版”概念。根据2010年《核酸研究》的数据库发布,2009-2010年生物数据库数量增长了约5%,在“GenBank”等主要数据库中,数据量大约每18个月翻一番。由于生物数据的固有属性所带来的数据建模挑战,多种建模工具如“增强实体关系”图和“统一建模语言”被用于建模生物迷你世界。为了与不同的数据模型兼容,生物数据库开发人员也使用了多种实现方法,即“平面文件”、“XML”、“关系数据库”、“面向对象数据库”、“ASN”。1’等等。坚持简单和保守的技术为生物数据库建模和实现提供了更好的实用方法。尽管生物数据库在内部数据模型、实现方法和生物范围上有所不同,但它们几乎都共享类似的三层web架构。这种相似性是当前用于数据库集成的三种主要策略的基础,即“链接/超文本集成”、“视图集成”和“数据仓库”。管理分子生物学研究和数据库的伦理框架需要重新设计,以适应这一迅速发展的科学领域所提出的要求。斯里兰卡生物医学信息学杂志2012;3 (1):2-11 DOI: http://dx.doi.org/10.4038/sljbmi.v3i1.2489
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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