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A methodology for the development of RESTful semantic web services for gene expression analysis

Gene expression studies are generally performed through multi-step analysis processes, which require the integrated use of a number of analysis tools. In order to facilitate tool/data integration, an increasing number of analysis tools have been developed as or adapted to semantic web services. In recent years, some approaches have been defined for the development and semantic annotation of web services created from legacy software tools, but these approaches still present many limitations. In addition, to the best of our knowledge, no suitable approach has been defined for the functional genomics domain. Therefore, this paper aims at defining an integrated methodology for the implementation of RESTful semantic web services created from gene expression analysis tools and the semantic annotation of such services. We have applied our methodology to the development of a number of services to support the analysis of different types of gene expression data, including microarray and RNASeq. All developed services are publicly available in the Gene Expression Analysis Services (GEAS) Repository at http://dcm.ffclrp.usp.br/lssb/geas. Additionally, we have used a number of the developed services to create different integrated analysis scenarios to reproduce parts of two gene expression studies documented in the literature. The first study involves the analysis of one-color microarray data obtained from multiple sclerosis patients and healthy donors. The second study comprises the analysis of RNA-Seq data obtained from melanoma cells to investigate the role of the remodeller BRG1 in the proliferation and morphology of these cells. Our methodology provides concrete guidelines and technical details in order to facilitate the systematic development of semantic web services. Moreover, it encourages the development and reuse of these services for the creation of semantically integrated solutions for gene expression analysis.

Semantic integration of gene expression analysis tools and data sources using software connectors

BackgroundThe study and analysis of gene expression measurements is the primary focus of functional genomics. Once expression data is available, biologists are faced with the task of extracting (new) knowledge associated to the underlying biological phenomenon. Most often, in order to perform this task, biologists execute a number of analysis activities on the available gene expression dataset rather than a single analysis activity. The integration of heteregeneous tools and data sources to create an integrated analysis environment represents a challenging and error-prone task. Semantic integration enables the assignment of unambiguous meanings to data shared among different applications in an integrated environment, allowing the exchange of data in a semantically consistent and meaningful way. This work aims at developing an ontology-based methodology for the semantic integration of gene expression analysis tools and data sources. The proposed methodology relies on software connectors to support not only the access to heterogeneous data sources but also the definition of transformation rules on exchanged data.ResultsWe have studied the different challenges involved in the integration of computer systems and the role software connectors play in this task. We have also studied a number of gene expression technologies, analysis tools and related ontologies in order to devise basic integration scenarios and propose a reference ontology for the gene expression domain. Then, we have defined a number of activities and associated guidelines to prescribe how the development of connectors should be carried out. Finally, we have applied the proposed methodology in the construction of three different integration scenarios involving the use of different tools for the analysis of different types of gene expression data.ConclusionsThe proposed methodology facilitates the development of connectors capable of semantically integrating different gene expression analysis tools and data sources. The methodology can be used in the development of connectors supporting both simple and nontrivial processing requirements, thus assuring accurate data exchange and information interpretation from exchanged data.

Semantic context reasoning using ontology based models

New mobile computing technologies and the increasing use of portable devices have pushed the development of the so-called context-aware applications. This new class of applications aims at improving human-computer interactions by supporting dynamic adaptations according to context changes. This paper discusses the suitability of using ontologies for modeling context information and presents the design, implementation and applicability of an ontology based context interpreter. The proposed interpreter is responsible for inferring new context information in a context-aware services platform.

Workflow automation based on OSI job transfer and manipulation

This paper shows that Workflow Management Systems (WFMS) and a data communication standard called Job Transfer and Manipulation (JTM) are built on the same concepts, even though different words are used. The paper analyses the correspondence of workflow concepts and JTM concepts. Besides, the correspondence of relationships between those concepts is analysed as well. Thus, we show that JTM is suitable for triggering activities, coordination of work, routing of documents, handling exceptions, safeguarding the integrity of business transactions and retrieving information from business processes. This implies that JTM can be used to support workflows and to provide interoperability between different brands of workflow tools.

A pattern-oriented specification of gene network inference processes

Patterns have been widely used in Computer Science. A pattern describes a generic solution to an existing problem in a more readable and accessible form. A pattern-oriented process specification consists of a generic and abstract description of a process. This paper presents a pattern-oriented specification of a genetic regulatory network inference process performed from microarray data and prior biological knowledge. The proposed specification was conceived based on prior work on gene inference networks. The adequacy of the proposed solution was then evaluated with respect to modern tendencies of the genes network inference literature.

Use of models and modelling techniques for service development

E-applications are increasingly being composed from individual services that can be realized with different technologies, such as, e.g., Web Services and standard component technologies. A current trend in the development of these services is to describe their technology-independent and technology-specific aspects in separate models. A prominent development that leads this trend is the Model-Driven Architecture (MDA). An important feature of the MDA approach is the explicit identification of Platform-Independent Models (PIMs) and the flexibility to implement them on different platforms via Platform-Specific Models (PSMs), possibly through (automated) model transformations. A platform can be any technology that supports the execution of these models, either directly or after translation to code in a programming language. This paper aims at identifying the benefits of the MDA approach in the development of services for e-applications. The paper presents a short introduction to MDA, in the context of service development, and an overview of the modelling capabilities of the Unified Modelling Language (UML), one of MDA’s main modelling languages.

OBO to UML: Support for the development of conceptual models in the biomedical domain

A conceptual model abstractly defines a number of concepts and their relationships for the purposes of understanding and communication. Once a conceptual model is available, it can also be used as a starting point for the development of a software system. The development of conceptual models using the Unified Modeling Language (UML) facilitates the representation of modeled concepts and allows software developers to directly reuse these concepts in the design of a software system. The OBO Foundry represents the most relevant collaborative effort towards the development of ontologies in the biomedical domain. The development of UML conceptual models in the biomedical domain may benefit from the use of domain-specific semantics and notation. Further, the development of these models may also benefit from the reuse of knowledge contained in OBO ontologies. This paper investigates the support for the development of conceptual models in the biomedical domain using UML as a conceptual modeling language and using the support provided by the OBO Foundry for the development of biomedical ontologies, namely entity kind and relationship types definitions provided by the Basic Formal Ontology (BFO) and the OBO Core Relations Ontology (OBO Core), respectively. Further, the paper investigates the support for the reuse of biomedical knowledge currently available in OBOFFF ontologies in the development these conceptual models. The paper describes a UML profile for the OBO Core Relations Ontology, which basically defines a number of stereotypes to represent BFO entity kinds and OBO Core relationship types definitions. The paper also presents a support toolset consisting of a graphical editor named OBO-RO Editor, which directly supports the development of UML models using the extensions defined by our profile, and a command-line tool named OBO2UML, which directly converts an OBOFFF ontology into a UML model.

SemanticSCo: a platform to support the semantic composition of services for gene expression analysis

Gene expression studies often require the combined use of a number of analysis tools. However, manual integration of analysis tools can be cumbersome and error prone. To support a higher level of automation in the integration process, efforts have been made in the biomedical domain towards the development of semantic web services and supporting composition environments. Yet, most environments consider only the execution of simple service behaviours and requires users to focus on technical details of the composition process. We propose a novel approach to the semantic composition of gene expression analysis services that addresses the shortcomings of the existing solutions. Our approach includes an architecture designed to support the service composition process for gene expression analysis, and a flexible strategy for the (semi) automatic composition of semantic web services. Finally, we implement a supporting platform called SemanticSCo to realize the proposed composition approach and demonstrate its functionality by successfully reproducing a microarray study documented in the literature. The SemanticSCo platform provides support for the composition of RESTful web services semantically annotated using SAWSDL. Our platform also supports the definition of constraints/conditions regarding the order in which service operations should be invoked, thus enabling the definition of complex service behaviours. Our proposed solution for semantic web service composition takes into account the requirements of different stakeholders and addresses all phases of the service composition process. It also provides support for the definition of analysis workflows at a high-level of abstraction, thus enabling users to focus on biological research issues rather than on the technical details of the composition process. The SemanticSCo source code is available at https://github.com/usplssb/SemanticSCo.

A case study on the transformation of context-aware domain data onto XML schemas

In order to accelerate the development of context-aware applications, it would be convenient to have a smooth path between the context models and the automated services that support these models. This paper discusses how MDA technology (metamodelling and the QVT standard) can support the transformation of high-level models of context-aware services onto the implementation of these services using web services. The total transformation process from context-aware services onto web services involves the following aspects: 1. service signatures, which should be translated onto WSDL definitions; 2. context-aware domain data used as input and output data in service operations, which should be translated onto XML schemas; and 3. service behaviours, which should be used to generate the service implementation. This paper concentrates on the modelling and transformation of the context-aware domain data. The results of this paper are generally applicable to the transformation of elements of any domain-specific language expressed in terms of a metamodel onto XML Schema data.