The FAIR Cookbook - the essential resource for and by FAIR doers.

The notion that data should be Findable, Accessible, Interoperable and Reusable, according to the FAIR Principles, has become a global norm for good data stewardship and a prerequisite for reproducibility. Nowadays, FAIR guides data policy actions and professional practices in the public and private sectors. Despite such global endorsements, however, the FAIR Principles are aspirational, remaining elusive at best, and intimidating at worst.

SBML Level 3: an extensible format for the exchange and reuse of biological models.

Systems biology has experienced dramatic growth in the number, size, and complexity of computational models. To reproduce simulation results and reuse models, researchers must exchange unambiguous model descriptions. We review the latest edition of the Systems Biology Markup Language (SBML), a format designed for this purpose.

BioSharing: curated and crowd-sourced metadata standards, databases and data policies in the life sciences.

BioSharing (http://www.biosharing.org) is a manually curated, searchable portal of three linked registries.

The Ontology for Biomedical Investigations.

The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide a representation of biomedical knowledge from the Open Biological and Biomedical Ontologies (OBO) project and adds the ability to describe how this knowledge was derived. We here describe the state of OBI and several applications that are using it, such as adding semantic expressivity to existing databases, building data entry forms, and enabling interoperability between knowledge resources.

The Software Ontology (SWO): a resource for reproducibility in biomedical data analysis, curation and digital preservation.

Motivation: Biomedical ontologists to date have concentrated on ontological descriptions of biomedical entities such as gene products and their attributes, phenotypes and so on. Recently, effort has diversified to descriptions of the laboratory investigations by which these entities were produced. However, much biological insight is gained from the analysis of the data produced from these investigations, and there is a lack of adequate descriptions of the wide range of software that are central to bioinformatics.

Controlled vocabularies and semantics in systems biology.

The use of computational modeling to describe and analyze biological systems is at the heart of systems biology. Model structures, simulation descriptions and numerical results can be encoded in structured formats, but there is an increasing need to provide an additional semantic layer. Semantic information adds meaning to components of structured descriptions to help identify and interpret them unambiguously.

Quantitative fitness analysis shows that NMD proteins and many other protein complexes suppress or enhance distinct telomere cap defects.

To better understand telomere biology in budding yeast, we have performed systematic suppressor/enhancer analyses on yeast strains containing a point mutation in the essential telomere capping gene CDC13 (cdc13-1) or containing a null mutation in the DNA damage response and telomere capping gene YKU70 (yku70Δ). We performed Quantitative Fitness Analysis (QFA) on thousands of yeast strains containing mutations affecting telomere-capping proteins in combination with a library of systematic gene deletion mutations. To perform QFA, we typically inoculate 384 separate cultures onto solid agar plates and monitor growth of each culture by photography over time.

Annotation of SBML models through rule-based semantic integration.

Background: The creation of accurate quantitative Systems Biology Markup Language (SBML) models is a time-intensive, manual process often complicated by the many data sources and formats required to annotate even a small and well-scoped model. Ideally, the retrieval and integration of biological knowledge for model annotation should be performed quickly, precisely, and with a minimum of manual effort.

Results: Here we present rule-based mediation, a method of semantic data integration applied to systems biology model annotation.

Managing experimental data using FuGE.

Data management and sharing in omics science is highly challenging due to the constant evolution of experimental techniques, the range of instrument types and software used for analysis, and the high volumes of data produced. The Functional Genomics Experiment (FuGE) Model was created to provide a model for capturing descriptions of sample processing, experimental protocols and multidimensional data for any kind of omics experiment. FuGE has two modes of action: (a) as a storage architecture for experimental workflows and (b) as a framework for building new technology-specific data standards.

Saint: a lightweight integration environment for model annotation.

Unlabelled: Saint is a web application which provides a lightweight annotation integration environment for quantitative biological models. The system enables modellers to rapidly mark up models with biological information derived from a range of data sources.

Availability And Implementation: Saint is freely available for use on the web at http://www.

Interfacing systems biology and synthetic biology.

A report of BioSysBio 2009, the IET conference on Synthetic Biology, Systems Biology and Bioinformatics, Cambridge, UK, 23-25 March 2009.

Modeling and managing experimental data using FuGE.

The Functional Genomics Experiment data model (FuGE) has been developed to increase the consistency and efficiency of experimental data modeling in the life sciences, and it has been adopted by a number of high-profile standardization organizations. FuGE can be used: (1) directly, whereby generic modeling constructs are used to represent concepts from specific experimental activities; or (2) as a framework within which method-specific models can be developed. FuGE is both rich and flexible, providing a considerable number of modeling constructs, which can be used in a range of different ways.

Meeting report: the fourth Genomic Standards Consortium (GSC) workshop.

This meeting report summarizes the proceedings of the "eGenomics: Cataloguing our Complete Genome Collection IV" workshop held June 6-8, 2007, at the National Institute for Environmental eScience (NIEeS), Cambridge, United Kingdom. This fourth workshop of the Genomic Standards Consortium (GSC) was a mix of short presentations, strategy discussions, and technical sessions. Speakers provided progress reports on the development of the "Minimum Information about a Genome Sequence" (MIGS) specification and the closely integrated "Minimum Information about a Metagenome Sequence" (MIMS) specification.

The minimum information about a genome sequence (MIGS) specification.

With the quantity of genomic data increasing at an exponential rate, it is imperative that these data be captured electronically, in a standard format. Standardization activities must proceed within the auspices of open-access and international working bodies. To tackle the issues surrounding the development of better descriptions of genomic investigations, we have formed the Genomic Standards Consortium (GSC).

The first RSBI (ISA-TAB) workshop: "can a simple format work for complex studies?".

This article summarizes the motivation for, and the proceedings of, the first ISA-TAB workshop held December 6-8, 2007, at the EBI, Cambridge, UK. This exploratory workshop, organized by members of the Microarray Gene Expression Data (MGED) Society's Reporting Structure for Biological Investigations (RSBI) working group, brought together a group of developers of a range of collaborative systems to discuss the use of a common format to address the pressing need of reporting and communicating data and metadata from biological, biomedical, and environmental studies employing combinations of genomics, transcriptomics, proteomics, and metabolomics technologies along with more conventional methodologies. The expertise of the participants comprised database development, data management, and hands-on experience in the development of data communication standards.