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

今天，生物科学正在产生大量的数据，旨在解决基本问题，如“生命的分子基础是什么？”生物体是如何工作的？疾病是如何产生的，如何治疗？'.虽然过去的研究经常遵循还原论的方法-研究部分以了解整体-但今天它越来越多地遵循系统方法，将过去的见解整合到有机体的整体模型（系统生物学）中。目标是使用这样一个模型来执行生物体的计算机模拟，并使用它来回答诸如“添加化合物X（例如药物）对生物体有什么影响？'.在分子科学的特定领域-基因（生命的密码）、蛋白质（有机体的化学工厂）和糖或药物等小分子的信息-组织数据的孤立方法将妨碍协同洞察力。相反，生物科学中用于参数化此类模拟的数据库需要相互关联和互操作，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世界范围内建立的，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，生物科学界正在研究共同的数据模型和标准。科学家们创建了关于如何在计算机中命名和编码科学信息的规则（语义学），以及这些信息的特定片段如何与其周围的科学概念（本体论）相关。这导致了本体链，例如“狐狸是哺乳动物，又是动物”，计算机自动推理狐狸是动物，即使没有明确说明。除了本体中实体之间所谓的“is_a”关系之外，还存在一系列其他关系，例如“is_part_of”，但这些关系可能仅在某些知识领域中相关。由于本体可以是复杂的，并且相邻领域的本体可能是相互关联的，因此它们允许机器对世界进行推理。生物学感兴趣的化学实体数据库（ChEBI）为生物科学界提供语义和本体信息以及小化学化合物（如大多数药物）的稳定标识符。药物发现或系统生物学等领域汇集了有关细胞，基因和蛋白质形态的信息，以及作用于这些的小分子。数据库中这些信息位之间的相互联系通常是通过标准化机构和数据库提供商分配给单个基因、蛋白质或小分子等实体的稳定标识符来实现的。此外，正式的和所谓的“平凡”的名称被分配并与数据库中的实体和稳定标识符相关联。ChEBI作为生物学感兴趣的小分子领域的此类名称和稳定标识符的资源。为此，它在生物科学界广泛使用，他们向ChEBI团队发送分配特定小分子实体标识符的正式请求，然后ChEBI团队执行分配，将信息发布到公共领域并通知请求方请求已得到满足。ChEBI还作为一个本体论，将小分子结构及其结构特性置于本体论背景下。它作出声明，如'D-葡萄糖是一种D-己醛糖，这是一种... [各种关系省略].它是一种单糖，也就是糖。再一次，像上面这样的本体链允许计算机对世界（在这种情况下是化学）做出陈述，这些陈述在其他地方没有被明确编码。例如，在文本挖掘领域，这是有用的，基于计算机的印刷文献中知识的重新发现。

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.