RESUMEN
This article describes some use case studies and self-assessments of FAIR status of de.NBI services to illustrate the challenges and requirements for the definition of the needs of adhering to the FAIR (findable, accessible, interoperable and reusable) data principles in a large distributed bioinformatics infrastructure. We address the challenge of heterogeneity of wet lab technologies, data, metadata, software, computational workflows and the levels of implementation and monitoring of FAIR principles within the different bioinformatics sub-disciplines joint in de.NBI. On the one hand, this broad service landscape and the excellent network of experts are a strong basis for the development of useful research data management plans. On the other hand, the large number of tools and techniques maintained by distributed teams renders FAIR compliance challenging.
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Manejo de Datos/métodos , Metadatos , Redes Neurales de la Computación , Proteómica/métodos , Programas Informáticos , Genoma Humano , Secuenciación de Nucleótidos de Alto Rendimiento , Humanos , Cooperación Internacional , Fenotipo , Plantas/genética , Proteoma , Autoevaluación (Psicología) , Flujo de TrabajoRESUMEN
SABIO-RK (http://sabiork.h-its.org/) is a manually curated database containing data about biochemical reactions and their reaction kinetics. The data are primarily extracted from scientific literature and stored in a relational database. The content comprises both naturally occurring and alternatively measured biochemical reactions and is not restricted to any organism class. The data are made available to the public by a web-based search interface and by web services for programmatic access. In this update we describe major improvements and extensions of SABIO-RK since our last publication in the database issue of Nucleic Acid Research (2012). (i) The website has been completely revised and (ii) allows now also free text search for kinetics data. (iii) Additional interlinkages with other databases in our field have been established; this enables users to gain directly comprehensive knowledge about the properties of enzymes and kinetics beyond SABIO-RK. (iv) Vice versa, direct access to SABIO-RK data has been implemented in several systems biology tools and workflows. (v) On request of our experimental users, the data can be exported now additionally in spreadsheet formats. (vi) The newly established SABIO-RK Curation Service allows to respond to specific data requirements.
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Fenómenos Bioquímicos , Bases de Datos de Compuestos Químicos , Animales , Curaduría de Datos , Enzimas/metabolismo , Humanos , Internet , Cinética , Redes y Vías Metabólicas , Motor de Búsqueda , Transducción de Señal , Interfaz Usuario-ComputadorRESUMEN
SABIO-RK (http://sabio.h-its.org/) is a web-accessible database storing comprehensive information about biochemical reactions and their kinetic properties. SABIO-RK offers standardized data manually extracted from the literature and data directly submitted from lab experiments. The database content includes kinetic parameters in relation to biochemical reactions and their biological sources with no restriction on any particular set of organisms. Additionally, kinetic rate laws and corresponding equations as well as experimental conditions are represented. All the data are manually curated and annotated by biological experts, supported by automated consistency checks. SABIO-RK can be accessed via web-based user interfaces or automatically via web services that allow direct data access by other tools. Both interfaces support the export of the data together with its annotations in SBML (Systems Biology Markup Language), e.g. for import in modelling tools.
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Fenómenos Bioquímicos , Bases de Datos Factuales , Enzimas/metabolismo , Internet , Cinética , Interfaz Usuario-ComputadorRESUMEN
SABIO-RK is a database for biochemical reactions and their kinetics. Data in SABIO-RK are inherently multidimensional and complex. The complex relationships between the data are often difficult to follow or even not represented when using standard tabular views. With an increasing number of data points the mismatch between tables and insights becomes more obvious, and getting an overview of the data becomes harder. Such complex data benefit from being presented using specially adapted visual tools. Visualization is a natural and user-friendly way to quickly get an overview of the data and to detect clusters and outliers. Here, we describe the implementation of a variety of visualization concepts into a common interface within the SABIO-RK biochemical reaction kinetics database. For that purpose, we use a heat map, parallel coordinates and scatter plots to allow the interactive visual exploration of general entry-based information of biochemical reactions and specific kinetic parameter values. Database URL https://sabiork.h-its.org/.
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Bases de Datos Factuales , CinéticaRESUMEN
The German Network for Bioinformatics Infrastructure (de.NBI) is a national and academic infrastructure funded by the German Federal Ministry of Education and Research (BMBF). The de.NBI provides (i) service, (ii) training, and (iii) cloud computing to users in life sciences research and biomedicine in Germany and Europe and (iv) fosters the cooperation of the German bioinformatics community with international network structures. The de.NBI members also run the German node (ELIXIR-DE) within the European ELIXIR infrastructure. The de.NBI / ELIXIR-DE training platform, also known as special interest group 3 (SIG 3) 'Training & Education', coordinates the bioinformatics training of de.NBI and the German ELIXIR node. The network provides a high-quality, coherent, timely, and impactful training program across its eight service centers. Life scientists learn how to handle and analyze biological big data more effectively by applying tools, standards and compute services provided by de.NBI. Since 2015, more than 300 training courses were carried out with about 6,000 participants and these courses received recommendation rates of almost 90% (status as of July 2020). In addition to face-to-face training courses, online training was introduced on the de.NBI website in 2016 and guidelines for the preparation of e-learning material were established in 2018. In 2016, ELIXIR-DE joined the ELIXIR training platform. Here, the de.NBI / ELIXIR-DE training platform collaborates with ELIXIR in training activities, advertising training courses via TeSS and discussions on the exchange of data for training events essential for quality assessment on both the technical and administrative levels. The de.NBI training program trained thousands of scientists from Germany and beyond in many different areas of bioinformatics.
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Biología Computacional/educación , Europa (Continente) , Alemania , HumanosRESUMEN
Collecting, curating, interlinking, and sharing high quality data are central to de.NBI-SysBio, the systems biology data management service center within the de.NBI network (German Network for Bioinformatics Infrastructure). The work of the center is guided by the FAIR principles for scientific data management and stewardship. FAIR stands for the four foundational principles Findability, Accessibility, Interoperability, and Reusability which were established to enhance the ability of machines to automatically find, access, exchange and use data. Within this overview paper we describe three tools (SABIO-RK, Excemplify, SEEK) that exemplify the contribution of de.NBI-SysBio services to FAIR data, models, and experimental methods storage and exchange. The interconnectivity of the tools and the data workflow within systems biology projects will be explained. For many years we are the German partner in the FAIRDOM initiative (http://fair-dom.org) to establish a European data and model management service facility for systems biology.
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Sistemas de Administración de Bases de Datos , Biología de Sistemas , Bases de Datos Factuales , Humanos , Programas InformáticosRESUMEN
The scientific literature contains a tremendous amount of kinetic data describing the dynamic behaviour of biochemical reactions over time. These data are needed for computational modelling to create models of biochemical reaction networks and to obtain a better understanding of the processes in living cells. To extract the knowledge from the literature, biocurators are required to understand a paper and interpret the data. For modellers, as well as experimentalists, this process is very time consuming because the information is distributed across the publication and, in most cases, is insufficiently structured and often described without standard terminology. In recent years, biological databases for different data types have been developed. The advantages of these databases lie in their unified structure, searchability and the potential for augmented analysis by software, which supports the modelling process. We have developed the SABIO-RK database for biochemical reaction kinetics. In the present review, we describe the challenges for database developers and curators, beginning with an analysis of relevant publications up to the export of database information in a standardized format. The aim of the present review is to draw the experimentalist's attention to the problem (from a data integration point of view) of incompletely and imprecisely written publications. We describe how to lower the barrier to curators and improve this situation. At the same time, we are aware that curating experimental data takes time. There is a community concerned with making the task of publishing data with the proper structure and annotation to ontologies much easier. In this respect, we highlight some useful initiatives and tools.