The corpus of bioinformatics resources is huge and expanding rapidly, presenting life scientists with a growing challenge in selecting tools that fit the desired purpose. To address this, the European Infrastructure for Biological Information is supporting a systematic approach towards a comprehensive registry of tools and databases for all domains of bioinformatics, provided under a single portal (https://bio.tools). We describe here the practical means by which scientific communities, including individual developers and projects, through major service providers and research infrastructures, can describe their own bioinformatics resources and share these via bio.tools.

MOTIVATION: Numerous software utilities operating on mass spectrometry (MS) data are described in the literature and provide specific operations as building blocks for the assembly of on-purpose workflows. Working out which tools and combinations are applicable or optimal in practice is often hard. Thus researchers face difficulties in selecting practical and effective data analysis pipelines for a specific experimental design. RESULTS: We provide a toolkit to support researchers in identifying, comparing and benchmarking multiple workflows from individual bioinformatics tools. Automated workflow composition is enabled by the tools' semantic annotation in terms of the EDAM ontology. To demonstrate the practical use of our framework, we created and evaluated a number of logically and semantically equivalent workflows for four use cases representing frequent tasks in MS-based proteomics. Indeed we found that the results computed by the workflows could vary considerably, emphasizing the benefits of a framework that facilitates their systematic exploration. AVAILABILITY AND IMPLEMENTATION: The project files and workflows are available from https://github.com/bio-tools/biotoolsCompose/tree/master/Automatic-Workflow-Composition. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Aspiring software developers, like the novice students in Computer Science courses, need to acquire a thorough understanding of fundamental computational concepts like sequential execution, conditional branching, loops, modularisation, hierarchy and reuse. This understanding and "computational thinking" is deepened when they encounter the concepts in different contexts and environments, as opposed to only in one traditional programming language. In this paper, we describe how we used the Cinco Adventure Game Tool, a tool that allows students to model simple browser games in an intuitive graphical framework, to train basic computational concepts in a creative and engaging, learning-by-doing fashion. On purpose, we steered away from traditional programming languages, in order to separate the use of the concepts and constructs from the hurdle of a programming language syntax and development environment. The experiences with a large group of first-term Computer Science students in two successive years were very positive: The students had no problems in understanding and using the concepts, used the tool proficiently and enjoyed designing and modelling the games. Working together on a game project in small groups, they showed sustained engagement, developed a high level of confidence, and created quite complex games containing various fundamental computational constructs.

We created a semantic domain model for a geographic data manipulation scenario (the creation of a topographic map of the Netherlands) in order to demonstrate what automated workflow composition can accomplish once suitable technical vocabularies and tool annotations are available. The classification of operations and types in the ontology is essential for effective usage of the automated composition framework, as it provides abstract terminology that the user can use to describe workflow at an abstract level. Most of the annotated tools in this case study belong to the GMT (Generic Mapping Tools). We then used the PROPHETS loose programming framework in order to specify and synthesize an executable workflow. The user provides the framework with constraints that describe desirable or undesirable features of the intended workflow (e.g. "use tool to draw water", "don’t use 3D plotting"). The framework translates this specification into a set of temporal logic constraints that are used as an input for the synthesis algorithm, together with the ontologies and tool annotations. The result of the synthesis is a workflow (or a set of different possible workflows) that fulfills the specification, allocating an annotated tool or a sequence of tools for each of the abstractions (e.g. "draw water" will be substituted with an actual tool).

Numerous software utilities operating on mass spectrometry (MS) data are described in the literature that provide specific operations as building blocks for the assembly of purpose-specific workflows. Working out which tools and combinations are applicable or optimal is often hard: insufficient annotation of tool functions and interfaces impedes finding viable tool combinations, and potentially compatible tools may not, in practice, operate together. Thus researchers face difficulties in selecting practical and effective data analysis pipelines for a specific experimental design.

We discuss how global types, aka multiparty session types, provide a complementary perspective on workflow models within the jABC modeling framework. On a reference example from the Semantic Web Services Challenge we show how the service orchestrations of jABC workflow applications can be expressed as service choreographies based on global types. Roles, identified with sets of logically related Service-Independent Building Blocks (SIBs), bridge between the two ways of looking at the behavior of systems. We compare the degree of declarativity and robustness in the face of changes of the reference example modeled with the jABC framework with as a global types specification.

Process modeling can play a central role in problem-based software development education with regard to qualifying students for the design and implementation of software applications for their specific needs without putting the focus on the technical part of coding. eXtreme Model Driven Design (XMDD) is a paradigm that focuses on the What (solving problems), rather than on the How (the technical skills of writing code). In this way it renders application design and implementation less daunting, thus accessible and more appealing to people that are either less technically skilled, or simply not interested at all in learning usual programming. In this paper we report on our experiences with the use of the jABC process modeling framework for teaching service-based software development in an XMDD fashion to students of different fields and on different levels of education.

In this paper, we sketch how treating product lines as systems of possibly heterogeneous constraints allows one to elegantly and consistently manage product lines in terms of a product line of product lines. In fact, as will also be illustrated along our example scenarios, this leads to a framework for a consistent division of labour in an "easy for the many difficult for the few" fashion which supports correctness by construction. Central for this approach are our powerful model-based synthesis and code generation technologies, which turn systems of constraints into executable models or target code.

SUMMARY In this article, we present our experience with over a decade of strict simplicity orientation in the development and evolution of plug‐ins. The point of our approach is to enable our graphical modeling framework jABC to capture plug‐in development in a domain‐specific setting. The typically quite tedious and technical plug‐in development is shifted this way from a programming task to the modeling level, where it can be mastered also by application experts without programming expertise. We show how the classical plug‐in development profits from a systematic domain‐specific API design and how the level of abstraction achieved this way can be further enhanced by defining adequate building blocks for high‐level plug‐in modeling. As the resulting plug‐in models can be compiled and deployed automatically, our approach decomposes plug‐in development into three phases where only the realization phase requires plug‐in‐specific effort. By using our modeling framework jABC, this effort boils down to graphical, tool‐supported process modeling. Furthermore, we support the automatic completion of process sketches for executability. All this will be illustrated along the most recent plug‐in‐based evolution of the jABC framework, which witnessed quite some bootstrapping effects. Copyright © 2013 John Wiley & Sons, Ltd.

PROPHETS is our flexible framework for the synthesis of processes from libraries of basic services. In this paper we demonstrate how its synthesis strategy can be tailored to the considered application domain. For this purpose, PROPHETS provides a number of configuration options, such as different data exchange formats (e.g. shared variables and pipe lining) for the resulting process, as well as structural and temporal logic constraints for minimizing the inherent search space. We illustrate the impact of adequate synthesis tailoring by contrasting two real-life case studies with diametric characteristics.

Traditional syntax-oriented variability modeling specifies the set of possible system variants by explicitly describing how variability is expressed by linguistic means and it concentrates on the set of features that may or may not be present in a product. In contrast, constraint-based variability modeling defines variability in a top-down way by restricting the set of possible compositions of reusable artifacts in terms of properties and by including in this declarative description also some behavioral knowledge the experts may have about the product. Concretely, we propose here to integrate constraint-based solution space variability modeling with feature-oriented problem space variability modeling. This new approach paves the way to significantly simplify feature-oriented software development of product lines: Each feature is described by a set of constraints capturing what the feature contributes to a product variant and expects from it, and, for a given feature selection, the set of associated feature constraints allows synthesizing the set of product variants satisfying the constraints automatically. We illustrate and evaluate the proposed approach on the concrete example of a family of workflows from the bioinformatics domain.

Bio-jETI is a framework for model-based, graphical development and execution of bioinformatics analysis processes. With the GeneSys code generation framework we can automatically compile the workflow models into native, stand-alone program code. We show via a phylogenetic analysis workflow designed by the DNA Data Bank of Japan (DDBJ) how we generate 6 variants of Java code from the corresponding process model realized in Bio-jETI. Performance measurements show that 1) the overall workflow execution time is dominated by the remote services it uses, and thus 2)all 6 variants are almost as fast as the handwritten Java of DDBJ. This way, we obtain efficient native code essentially without program- ming. Thus, we demonstrate in this paper that model- based workflow development in Bio-jETI offers several advantages over manual implementation – including higher agility, greater transparency and better maintainability – without compromising the runtime performance.

BACKGROUND: The development of bioinformatics databases, algorithms, and tools throughout the last years has lead to a highly distributed world of bioinformatics services. Without adequate management and development support, in silico researchers are hardly able to exploit the potential of building complex, specialized analysis processes from these services. The Semantic Web aims at thoroughly equipping individual data and services with machine-processable meta-information, while workflow systems support the construction of service compositions. However, even in this combination, in silico researchers currently would have to deal manually with the service interfaces, the adequacy of the semantic annotations, type incompatibilities, and the consistency of service compositions. RESULTS: In this paper, we demonstrate by means of two examples how Semantic Web technology together with an adequate domain modelling frees in silico researchers from dealing with interfaces, types, and inconsistencies. In Bio-jETI, bioinformatics services can be graphically combined to complex services without worrying about details of their interfaces or about type mismatches of the composition. These issues are taken care of at the semantic level by Bio-jETI's model checking and synthesis features. Whenever possible, they automatically resolve type mismatches in the considered service setting. Otherwise, they graphically indicate impossible/incorrect service combinations. In the latter case, the workflow developer may either modify his service composition using semantically similar services, or ask for help in developing the missing mediator that correctly bridges the detected type gap. Newly developed mediators should then be adequately annotated semantically, and added to the service library for later reuse in similar situations. CONCLUSION: We show the power of semantic annotations in an adequately modelled and semantically enabled domain setting. Using model checking and synthesis methods, users may orchestrate complex processes from a wealth of heterogeneous services without worrying about interfaces and (type) consistency. The success of this method strongly depends on a careful semantic annotation of the provided services and on its consequent exploitation for analysis, validation, and synthesis. We are convinced that these annotations will become standard, as they will become preconditions for the success and widespread use of (preferred) services in the Semantic Web.

BACKGROUND: PCR primer design is an everyday, but not trivial task requiring state-of-the-art software. We describe the popular tool GeneFisher and explain its recent restructuring using workflow techniques. We apply a service-oriented approach to model and implement GeneFisher-P, a process-based version of the GeneFisher web application, as a part of the Bio-jETI platform for service modeling and execution. We show how to introduce a flexible process layer to meet the growing demand for improved user-friendliness and flexibility. RESULTS: Within Bio-jETI, we model the process using the jABC framework, a mature model-driven, service-oriented process definition platform. We encapsulate remote legacy tools and integrate web services using jETI, an extension of the jABC for seamless integration of remote resources as basic services, ready to be used in the process. Some of the basic services used by GeneFisher are in fact already provided as individual web services at BiBiServ and can be directly accessed. Others are legacy programs, and are made available to Bio-jETI via the jETI technology. The full power of service-based process orientation is required when more bioinformatics tools, available as web services or via jETI, lead to easy extensions or variations of the basic process. This concerns for instance variations of data retrieval or alignment tools as provided by the European Bioinformatics Institute (EBI). CONCLUSIONS: The resulting service- and process-oriented GeneFisher-P demonstrates how basic services from heterogeneous sources can be easily orchestrated in the Bio-jETI platform and lead to a flexible family of specialized processes tailored to specific tasks.