Norwich BioScience Institutes

InterPro (http://www.ebi.ac.uk/interpro/) is a freely available database used to classify protein sequences into families and to predict the presence of important domains and sites. The resource is based around diagnostic models (profile hidden Markov models, profiles, position-specific scoring matrices and regular expressions) provided by 14 different member databases, against which protein sequences are searched to determine their potential functions. Two recently added member databases, CDD and SLFD, also provide specific residue-level annotation. Their addition has enabled identification of important amino acids, such as those responsible for ligand-binding, protein-protein interactions, or comprising active sites, providing an additional tier to the annotations already provided by InterPro. In a further expansion, InterPro has also added prediction of intrinsically disordered regions (IDRs) – polypeptide segments that have little or no three-dimensional structure. IDRs have a wide range of potential functions, from acting as flexible linkers between domains, to interacting with other proteins and modifying their activity. Due to their bias composition and differing pattern of amino acid conservation, IDRs are hard to model using profile approaches, hence annotation of these regions has been limited to date. To address this, InterPro has integrated the MobiDB Lite tool, which combines eight different prediction methods to generate consensus IDR annotations, focusing on long disordered regions (>20 amino acids). This approach has yielded IDR annotations for ~ 24% of sequences in UniProtKB, covering ~ 5.5% of amino acid residues. Here we describe how the new per-residue and IDR developments in InterPro enable more richly-detailed and informative annotation of protein sequences, and how they can be used to support more specific functional inferences.

EBI Metagenomics ( https://www.ebi.ac.uk/metagenomics/ ) is a freely available hub for the analysis and exploration of metagenomic, metatranscriptomic, amplicon and assembly data. The resource provides rich functional and taxonomic analyses of user-submitted sequences, as well as analysis of publicly available metagenomic datasets held within the European Nucleotide Archive. This presentation provides an overview of the resource and analysis pipeline components. It also outlines ways in which the resource can be used for data discovery and describes a number of recently added and forthcoming functionalities.

ISBE will empower the experimental research community to make modelling part of their lab routine. Here we discuss how to define and structure ISBE modelling services, building on D8.2's review of the purpose and overall design principles for modelling services. We identify the components of ISBE modelling services and propose an organizational structure to achieve uniform coverage of services from a heterogeneous network of expertises. A roadmap concludes the report, proposing initial low-budget services for selected modelling frameworks, then outlining a strategy for growth and scalability of ISBE modelling services. How to define and structure ISBE modelling services is a many-faceted question. First and foremost, one must identify the <em>purpose</em> of each service (what will it achieve?), which also entails specifying its <em>inputs and outputs</em>. It can be useful to group <em>kinds of services</em> into broader categories, either based on their <em>function</em>, or based on their <em>organizational structure</em> including staffing and funding. Modelling services will include automated analyses of published or user-provided models, fitting of parameters to user data, and refinement and adaptation of existing models. However, it also makes sense to include related services such as stewardship and training in the broad term "modelling services". A coordinating Systems Biology Centre (cSBC) will interconnect national Systems Biology Centres (nSBCs) to make the collective expertise of participating nations easily accessible for all European researchers. Chapter 2.3 concretizes this with illustrations of the variety of modelling services that ISBE is likely to offer, and how to route requests from clients to ISBE tools and expertise. Levels of service may range from fully automatic tools to long-term per­sonal involvement, with access to more demanding services prioritized in cooperation with funders. Likewise, there will be several kinds and levels of documentation and user support. We advocate a focus on user needs in prioritizing what ISBE is to offer, in specifying services, and in routing expertise to clients. Clear descriptions of the data requirements for each modelling approach helps clients figure out their options and see what additional data they might require to open more options for modelling. Standardized virtual experiments can form an articulated link between modellers and experimentalists, and can be used to stream­line the confrontation of models with data, e.g. in parameter estimation and model selection. As candidates for pilot services to be offered by the interim "ISBE light", we have identified modelling frameworks that span a wide range of biologically interesting questions within a well-defined set of user inputs. These include ordinary differential equations (where the rates-of-change of state variables is a function of the current value of those state variables) and constraint-based models (based on stoichiometry in biochemical reaction networks). The demand for modelling services is anticipated to increase sharply once ISBE succeeds in transforming the practice of biological research and application. To meet this demand, we identify five key issues of scalability: Recruitment of providers, routing of clients to providers, strategic focusing of effort, training and education of users, and standardization and curation to streamline knowledge management, each of which is detailed in Chapter 5.2.