SEMEDA: ontology based semantic integration of biological databases

MOTIVATION: Many molecular biological databases are implemented on relational Database Management Systems, which provide standard interfaces like JDBC and ODBC for data and metadata exchange. By using these interfaces, many technical problems of database integration vanish and issues related to semantics remain, e.g. the use of different terms for the same things, different names for equivalent database attributes and missing links between relevant entries in different databases. RESULTS: In this publication, principles and methods that were used to implement SEMEDA (Semantic Meta Database) are described. Database owners can use SEMEDA to provide semantically integrated access to their databases as well as to collaboratively edit and maintain ontologies and controlled vocabularies. Biologists can use SEMEDA to query the integrated databases in real time without having to know the structure or any technical details of the underlying databases. AVAILABILITY: SEMEDA is available at http://www-bm.ipk-gatersleben.de/semeda/. Database providers who intend to grant access to their databases via SEMEDA are encouraged to contact the authors.     

Turning text into research networks: information retrieval and computational ontologies in the creation of scientific databases

Background

Web-based, free-text documents on science and technology have been increasing growing on the web. However, most of these documents are not immediately processable by computers slowing down the acquisition of useful information. Computational ontologies might represent a possible solution by enabling semantically machine readable data sets. But, the process of ontology creation, instantiation and maintenance is still based on manual methodologies and thus time and cost intensive.

Method

We focused on a large corpus containing information on researchers, research fields, and institutions. We based our strategy on traditional entity recognition, social computing and correlation. We devised a semi automatic approach for the recognition, correlation and extraction of named entities and relations from textual documents which are then used to create, instantiate, and maintain an ontology.

Results

We present a prototype demonstrating the applicability of the proposed strategy, along with a case study describing how direct and indirect relations can be extracted from academic and professional activities registered in a database of curriculum vitae in free-text format. We present evidence that this system can identify entities to assist in the process of knowledge extraction and representation to support ontology maintenance. We also demonstrate the extraction of relationships among ontology classes and their instances.

Conclusion

We have demonstrated that our system can be used for the conversion of research information in free text format into database with a semantic structure. Future studies should test this system using the growing number of free-text information available at the institutional and national levels.     

生物医学领域本体的构建、评估与应用

介绍了本体的概念和基本特点, 总结了领域本体的一般构建流程和评估方法, 并举例说明了生物医学领域本体在生物学对象注释、富集分析、数据整合、数据库构建、图书馆建设、文本挖掘等方面的实际应用情况, 整理了目前常用的生物医学领域本体数据库、本体描述语言和本体编辑软件, 最后探讨了目前生物医学领域本体研究中普遍存在的问题和该领域未来的发展方向.     

A knowledge-based system for discovering ecological interactions in biodiversity data-stores of heterogeneous specimen-records: A case-study of flower-visiting ecology

We modeled expert knowledge of arthropod flower-visiting behavioral ecology and represented this in an event-centric domain ontology, which we describe along with the ontology construction process. Two smaller domain ontologies were created to represent expert knowledge of known flower-visiting insect groups and expert knowledge of the flower-visiting behavioral ecology of Rediviva bees. Two application ontologies were designed, which, together with the domain ontologies, constituted the ontology framework of a prototype semantic enrichment and mediation system that we designed and implemented to improve semantic interoperability between flower-visiting data-stores. We describe and evaluate the system implementation in a case-study of three flower-visiting data-stores, and we discuss the system's scalability, extension and potential impact. We demonstrate how the system is able to dynamically extract complex ecological interactions from heterogeneous specimen data-stores. The conceptual stance and modeling approach are potentially of general use in representing knowledge of animal behavior and ecological interactions, and in engineering semantic interoperability between data-stores containing behavioral ecology data.     

Physical properties of biological entities: an introduction to the ontology of physics for biology

As biomedical investigators strive to integrate data and analyses across spatiotemporal scales and biomedical domains, they have recognized the benefits of formalizing languages and terminologies via computational ontologies. Although ontologies for biological entities-molecules, cells, organs-are well-established, there are no principled ontologies of physical properties-energies, volumes, flow rates-of those entities. In this paper, we introduce the Ontology of Physics for Biology (OPB), a reference ontology of classical physics designed for annotating biophysical content of growing repositories of biomedical datasets and analytical models. The OPB's semantic framework, traceable to James Clerk Maxwell, encompasses modern theories of system dynamics and thermodynamics, and is implemented as a computational ontology that references available upper ontologies. In this paper we focus on the OPB classes that are designed for annotating physical properties encoded in biomedical datasets and computational models, and we discuss how the OPB framework will facilitate biomedical knowledge integration.     

OntoBlast function: From sequence similarities directly to potential functional annotations by ontology terms

OntoBlast allows one to find information about potential functions of proteins by presenting a weighted list of ontology entries associated with similar sequences from completely sequenced genomes identified in a BLAST search. It combines, in a single analysis step, the search for sequence similarities in several species with the association of information stored in ontologies. From each identified ontology term a list of genes, which share the functional annotation, can be retrieved. The OntoBlast function is an integral part of the 'Ontologies TO GenomeMatrix' tool which provides an alternative entry point from ontology terms to the Genome-Matrix database. OntoBlast's web interface is accessible on the 'Ontologies TO GenomeMatrix Gate' page at http://functionalgenomics.de/ontogate/.     

SIDD: A Semantically Integrated Database towards a Global View of Human Disease

Background

A number of databases have been developed to collect disease-related molecular, phenotypic and environmental features (DR-MPEs), such as genes, non-coding RNAs, genetic variations, drugs, phenotypes and environmental factors. However, each of current databases focused on only one or two DR-MPEs. There is an urgent demand to develop an integrated database, which can establish semantic associations among disease-related databases and link them to provide a global view of human disease at the biological level. This database, once developed, will facilitate researchers to query various DR-MPEs through disease, and investigate disease mechanisms from different types of data.

Methodology

To establish an integrated disease-associated database, disease vocabularies used in different databases are mapped to Disease Ontology (DO) through semantic match. 4,284 and 4,186 disease terms from Medical Subject Headings (MeSH) and Online Mendelian Inheritance in Man (OMIM) respectively are mapped to DO. Then, the relationships between DR-MPEs and diseases are extracted and merged from different source databases for reducing the data redundancy.

Conclusions

A semantically integrated disease-associated database (SIDD) is developed, which integrates 18 disease-associated databases, for researchers to browse multiple types of DR-MPEs in a view. A web interface allows easy navigation for querying information through browsing a disease ontology tree or searching a disease term. Furthermore, a network visualization tool using Cytoscape Web plugin has been implemented in SIDD. It enhances the SIDD usage when viewing the relationships between diseases and DR-MPEs. The current version of SIDD (Jul 2013) documents 4,465,131 entries relating to 139,365 DR-MPEs, and to 3,824 human diseases. The database can be freely accessed from: http://mlg.hit.edu.cn/SIDD.     

Ontologies: Formalising biological knowledge for bioinformatics

An ontology is a domain of knowledge structured through formal rules so that it can be interpreted and used by computers. Ontologies are becoming increasingly important in bioinformatics because they can be linked to the information in databases and their knowledge then used to query the databases. Typical examples in current use are the Gene Ontology, which incorporates much of our knowledge about gene products, and ontologies of developmental anatomy, which, for example, facilitate tissue-based queries to gene expression databases both textually and spatially. This article considers the production, formulation and types of bio-ontologies together with the reasons why they are so useful.     

Integrating phenotype ontologies across multiple species

Phenotype ontologies are typically constructed to serve the needs of a particular community, such as annotation of genotype-phenotype associations in mouse or human. Here we demonstrate how these ontologies can be improved through assignment of logical definitions using a core ontology of phenotypic qualities and multiple additional ontologies from the Open Biological Ontologies library. We also show how these logical definitions can be used for data integration when combined with a unified multi-species anatomy ontology.     

一种基于本体集成的生物医学数据库中语义映射维护方法研究

生物医学数据库到生物医学本体的语义映射是基于本体集成生物医学数据库系统的一个重要环节.而生物医学本体随着学科的发展不断演化,造成了集成系统不稳定.针对这个问题,本文在本体演化条件下,分析并发现了语义映射的变化规律,设计了对应的维护流程和维护方法,并通过计算维护收益率证明了该方法对映射的维护是有效性的,从而增强了集成系统在本体演化条件下的稳定性.     

SPARQL Assist language-neutral query composer

Background

More than one million terms from biomedical ontologies and controlled vocabularies are available through the Ontology Lookup Service (OLS). Although OLS provides ample possibility for querying and browsing terms, the visualization of parts of the ontology graphs is rather limited and inflexible.

Results

We created the OLSVis web application, a visualiser for browsing all ontologies available in the OLS database. OLSVis shows customisable subgraphs of the OLS ontologies. Subgraphs are animated via a real-time force-based layout algorithm which is fully interactive: each time the user makes a change, e.g. browsing to a new term, hiding, adding, or dragging terms, the algorithm performs smooth and only essential reorganisations of the graph. This assures an optimal viewing experience, because subsequent screen layouts are not grossly altered, and users can easily navigate through the graph. URL: http://ols.wordvis.com

Conclusions

The OLSVis web application provides a user-friendly tool to visualise ontologies from the OLS repository. It broadens the possibilities to investigate and select ontology subgraphs through a smooth visualisation method.     

一种基于本体集成的生物医学数据库中语义映射维护方法研究

生物医学数据库到生物医学本体的语义映射是基于本体集成生物医学数据库系统的一个重要环节。而生物医学本体随着学科的发展不断演化,造成了集成系统不稳定。针对这个问题,本文在本体演化条件下,分析并发现了语义映射的变化规律,设计了对应的维护流程和维护方法,并通过计算维护收益率证明了该方法对映射的维护是有效性的,从而增强了集成系统在本体演化条件下的稳定性。     

Representing genetic sequence data for pharmacogenomics: an evolutionary approach using ontological and relational models

MOTIVATION: The information model chosen to store biological data affects the types of queries possible, database performance, and difficulty in updating that information model. Genetic sequence data for pharmacogenetics studies can be complex, and the best information model to use may change over time. As experimental and analytical methods change, and as biological knowledge advances, the data storage requirements and types of queries needed may also change. RESULTS: We developed a model for genetic sequence and polymorphism data, and used XML Schema to specify the elements and attributes required for this model. We implemented this model as an ontology in a frame-based representation and as a relational model in a database system. We collected genetic data from two pharmacogenetics resequencing studies, and formulated queries useful for analysing these data. We compared the ontology and relational models in terms of query complexity, performance, and difficulty in changing the information model. Our results demonstrate benefits of evolving the schema for storing pharmacogenetics data: ontologies perform well in early design stages as the information model changes rapidly and simplify query formulation, while relational models offer improved query speed once the information model and types of queries needed stabilize.