Continued development of the ChEBI database and ontology for improved interoperability with biomedical resources

今天，生物科学正在产生海量的数据，旨在解决一些基本问题，如‘生命的分子基础是什么？’，‘生物体是如何工作的？’以及“疾病是如何产生的，如何治疗？”虽然过去的研究通常遵循简化论的方法--研究部分以了解整体--但今天它越来越遵循系统方法，将过去的见解整合到有机体的整体模型(系统生物学)中。我们的目标是使用这样的模型来对生物体进行计算机模拟，并用它来回答这样的问题，例如：添加化合物X(例如药物)会对生物体产生什么影响？在分子科学的特定领域组织数据的孤立方法-关于基因(生命的密码)、蛋白质(生物体的化学工厂)和小分子(如糖或药物)的信息-将阻碍协同洞察。相反，用于将这种模拟参数化的生物科学中的数据库需要相互链接和可互操作，允许它们之间的无缝移动。由于生物数据库是由不同的社区在全球范围内生成的，它们的整合带来了明显的挑战。因此，除了互操作性的简单技术问题外，生物科学界还在致力于共同的数据模型和标准。科学家们制定了关于如何在计算机中命名和编码科学信息(语义)以及此类信息的特定部分如何与其周围的科学概念(本体论)相关的规则。这就产生了本体链，比如“狐狸是哺乳动物，而狐狸又是动物”，即使没有明确说明，计算机也会自动推论狐狸是动物。除了本体论中实体之间的所谓‘is_a’关系之外，还存在诸如‘is_part_of’之类的一系列其他关系，但这些关系可能只与某些知识领域相关。由于本体论可能很复杂，而且相邻领域的本体论可能是相互关联的，它们允许机器对世界进行推理。生物兴趣化学实体数据库(CHECBI)提供了生物科学界的语义和本体论信息，以及小化合物(大多数药物也是如此)的稳定识别符。药物发现或系统生物学等领域汇集了有关细胞、基因和蛋白质的形态以及作用于这些物质的小分子的信息。数据库中这些信息位之间的链接通常是通过标准化机构和数据库提供商分配给诸如单基因、蛋白质或小分子等实体的稳定识别符来实现的。此外，分配正式的和所谓的“琐碎”名称，并将其与数据库中的实体和稳定标识符相关联。Chebi在生物感兴趣的小分子领域充当了这样的名字和稳定的识别符的资源。为此，它在生物科学界被广泛使用，他们向Chebi团队发送分配特定小分子实体的识别符的正式请求，然后由Chebi团队执行分配，将信息公布到公共领域，并通知请求方请求已完成。作为一种本体论，契比将小分子结构及其结构属性置于本体论的背景下。它做出了这样的陈述：‘D-葡萄糖是一种D-醛己糖，它是一种糖……[省略了各种关系]……它是一种单糖，它是一种糖。同样，像上面这样的本体论链允许计算机对世界(在这种情况下是化学的)做出陈述，而这些陈述在其他地方没有被明确编码。例如，这在文本挖掘领域是有用的，文本挖掘是对印刷文献中知识的基于计算机的重新发现。

Today, the biological sciences are generating an enormous amount of data aimed at tackling fundamental questions such as 'What is the molecular basis for life?', 'How do organisms work?' and 'How does disease arise and how can it be treated?'. While research in the past has often followed a reductionist approach - studying the parts to understand the whole - today it increasingly follows a systems approach, integrating insights from the past into a holistic model of an organism (systems biology). The goal is to use such a model to perform a computer simulation of the organism and to use this to answer questions such as 'What effect will the addition of compound X (for example a drug) have on the organism?'. Isolated approaches to organizing the data in particular fields in the molecular sciences - information on genes (the code of life), proteins (an organism's chemical factories) and small molecules such as sugars or drugs - will hamper synergistic insights. Instead, databases in the biological sciences, which are used to parametrize such simulations, need to be interlinked and interoperable, allowing seamless movement amongst them. Because biological databases are generated on a worldwide basis by diverse communities, their integration creates obvious challenges. Besides simple technical questions of interoperability, the bioscience community is therefore working on common data models and standards. Scientists create rules on how to name and encode scientific information in a computer (semantics) and how a particular piece of such information relates to the scientific concepts in its surroundings (ontologies). This results in ontological chains such as 'A fox is_a mammal, which again is_a animal', from which the computer automatically reasons that a fox is an animal, even if this is not explicitly stated. Besides the so-called 'is_a' relationship between entities in ontologies, there exists a whole range of other relationships such as 'is_part_of', but which may be relevant only in certain fields of knowledge. Since ontologies can be complex and those of neighbouring fields may be interlinked, they allow machines to reason about the world. The database Chemical Entities of Biological Interest (ChEBI) provides for the bioscientific community semantic and ontological information as well as stable identifiers for small chemical compounds (as are most drugs). Areas such as drug discovery or systems biology bring together information about the morphology of cells, genes and proteins, as well as the small molecules that act on these. The interlinking between these bits of information in databases is typically performed through stable identifiers assigned to entities such as single genes, proteins or small molecules by standardization bodies and database providers. In addition, formal and so-called 'trivial' names are assigned and associated with both the entity and the stable identifier in the database. ChEBI acts as a resource for such names and stable identifiers in the area of small molecules of biological interest. For this purpose it is widely used in the bioscience community, who send formal requests for the assignment of identifiers for particular small molecule entities to the ChEBI team, who then perform the assignment, publish the information into the public domain and inform the requesting party that the request has been fulfilled. Also acting as an ontology, ChEBI puts small molecule structures and their structural properties into an ontological context. It makes statements such as 'D-Glucose is_a D-aldohexose, which is_a ... [various is_a relationships omitted] ... which is_a monosaccharide, which is_a sugar.' Again, ontological chains such as the one above allow computers to make statements about the world (of chemistry in this case), which have not been explicitly coded elsewhere. This is useful, for example, in the field of text mining, the computer-based re-discovery of knowledge in the printed literature.