Ontology based data integration in life sciences

El objetivo de la tesis es el desarrollo de una solución práctica y estándar para la integración semántica de los datos y servicios biológicos. La tesis estudia escenarios diferentes en los cuales las ontologías pueden beneficiar el desarrollo de los servicios web, su búsqueda y su visibilidad. A pesar de que las ontologías son ampliamente utilizadas en la biología, su uso habitualmente se limita a la definición de las jerarquías taxonómicas. La tesis examina la utilidad de las ontologías para la integración de los datos en el desarrollo de los servicios web semánticos. Las ontologías que definen los tipos de datos biológicos tienen un gran valor para la integración de los datos, especialmente ante un cambio continuo de los estándares. La tesis evalúa la ontología BioMoby para la generación de los servicios web conforme con las especificaciones WS-I y los servicios REST. Otro aspecto muy importante de la tesis es el uso de las ontologías para la descripción de los servicios web. La tesis evalúa la ontología WSDL promovida por el consorcio W3C para la descripción de los servicios y su búsqueda. Finalmente, se considera la integración con las plataformas modernas de la ejecución de los flujos de trabajo como Taverna y Galaxy. A pesar de la creciente popularidad del formato JSON, los servicios web dependen mucho del XML. La herramienta OWL2XS facilita el desarrollo de los servicios web semánticos generando un esquema XML a partir de una ontología OWL 2. La integración de los servicios web es difícil de conseguir sin una adaptación de los estándares. La aplicación BioNemus genera de manera automática servicios web estándar a partir de las ontologías BioMoby. La representación semántica de los servicios web simplifica su búsqueda y anotación. El Registro Semántico de Servicios Web (BioSWR) está basado en la ontología WSDL del W3C y proporciona una representación en distintos formatos: OWL 2, WSDL 1.1, WSDL 2.0 y WADL. Para demostrar los beneficios de la descripción semántica de los servicios web se ha desarrollado un plugin para Taverna. También se ha implementado una nueva librería experimental que ha sido usada en la aplicación Galaxy Gears, la cual permite la integración de los servicios web en Galaxy. La tesis explora el alcance de la aplicación de las ontologías para la integración de los datos y los servicios biológicos, proporcionando un amplio conjunto de nuevas aplicaciones.The aim of this thesis is to develop standard and practical approaches for the semantic integration of biological data and services. The thesis considers various scenarios where ontologies may benefit bioinformatics web services development, integration and provenance. In spite of the broad use of ontologies in biology, their usage is usually limited to a definition of taxonomic hierarchies. This thesis examines the utility of ontologies for data integration in context of semantic web services development. The biological datatypes ontologies are very valuable for the data integration, especially in a context of continuous standards changes. The thesis evaluates the outdated BioMoby ontology for the generation of modern WS-I and RESTful web services. Another important aspect is the use of ontologies for the web services description. The thesis evaluates the W3C standard WSDL ontology for bioinformatics web services description and provenance. Finally, the integration with modern workflow execution platforms such as Taverna and Galaxy is also considered. Despite the growing popularity of JSON format, web services vastly depend on XML type system. The OWL2XS tool facilitates semantic web services development providing the automatic XML Schema generation from an appropriate OWL 2 datatype ontology. Web services integration is hardly achievable without a broad standard adoption. The BioNemus application automatically generates standard-based web services from BioMoby ontologies. Semantic representation of web services description simplifies web services search and annotation. Semantic Web Services Registry (BioSWR) is based on W3C WSDL ontology and provides a multifaceted web services view in different formats: OWL 2, WSDL 1.1, WSDL 2.0 and WADL. To demonstrate benefits of ontology-based web services descriptions, BioSWR Taverna OSGI plug-in has been developed. The new, experimental, Taverna WSDL generic library has been used in Galaxy Gears tool which allows integrating web services into the Galaxy workflows. The thesis explores the scopes of ontologies application for the biological data and services integration, providing a broad set of original tools

Data integration in the era of omics: current and future challenges

To integrate heterogeneous and large omics data constitutes not only a conceptual challenge but a practical hurdle in the daily analysis of omics data. With the rise of novel omics technologies and through large-scale consortia projects, biological systems are being further investigated at an unprecedented scale generating heterogeneous and often large data sets. These data-sets encourage researchers to develop novel data integration methodologies. In this introduction we review the definition and characterize current efforts on data integration in the life sciences. We have used a web-survey to assess current research projects on data-integration to tap into the views, needs and challenges as currently perceived by parts of the research community

NeuroProv: Provenance data visualisation for neuroimaging analyses

© 2019 Elsevier Ltd Visualisation underpins the understanding of scientific data both through exploration and explanation of analysed data. Provenance strengthens the understanding of data by showing the process of how a result has been achieved. With the significant increase in data volumes and algorithm complexity, clinical researchers are struggling with information tracking, analysis reproducibility and the verification of scientific output. In addition, data coming from various heterogeneous sources with varying levels of trust in a collaborative environment adds to the uncertainty of the scientific outputs. This provides the motivation for provenance data capture and visualisation support for analyses. In this paper a system, NeuroProv is presented, to visualise provenance data in order to aid in the process of verification of scientific outputs, comparison of analyses, progression and evolution of results for neuroimaging analyses. The experimental results show the effectiveness of visualising provenance data for neuroimaging analyses

Data platforms for open life sciences-A systematic analysis of management instruments

Open data platforms are interfaces between data demand of and supply from their users. Yet, data platform providers frequently struggle to aggregate data to suit their users' needs and to establish a high intensity of data exchange in a collaborative environment. Here, using open life science data platforms as an example for a diverse data structure, we systematically categorize these platforms based on their technology intermediation and the range of domains they cover to derive general and specific success factors for their management instruments. Our qualitative content analysis is based on 39 in-depth interviews with experts employed by data platforms and external stakeholders. We thus complement peer initiatives which focus solely on data quality, by additionally highlighting the data platforms' role to enable data utilization for innovative output. Based on our analysis, we propose a clearly structured and detailed guideline for seven management instruments. This guideline helps to establish and operationalize data platforms and to best exploit the data provided. Our findings support further exploitation of the open innovation potential in the life sciences and beyond

Doctor of Philosophy

dissertationTopographic connections of retinal axons with their brain targets allow us to perceive a spatially organized image of the visual world. Achieving this precise retinotopic axon targeting during development first requires the patterning of origin (retina) and target (brain) tissues along anterior-posterior (A-P) and dorsal-ventral (D-V) axes, such that individual cells of both tissues acquire a molecularly specified positional identity. The research presented in my dissertation addresses the processes involved in patterning the dorsal-ventral axis of the retina and forming dorsal-ventral retinotopic projections. First, I studied what tissues and signals are involved in the initiation of dorsal polarity. I found that the dorsolateral region of the optic vesicle is the first domain to upregulate dorsal-specific transcription factors. My expression studies, combined with my fate map experiments, suggested that these dorsolateral optic vesicle cells continue expressing dorsal markers throughout optic vesicle morphogenesis, and eventually contribute to dorsal and central retina. I also showed that the BMP family gene gdf6a is necessary for initiation of dorsal retinal fate. Importantly, I found that gdf6a acts early during optic vesicle evagination (10-12 hpf) when it is expressed in the extraocular head ectoderm overlying the region of dorsolateral optic vesicle that first expresses dorsalspecific transcription factors. Finally, I showed that the bmp2b gene is also necessary for dorsal retinal fate initiation, acting upstream of gdf6a. iv Secondly, I performed a forward genetic screen to search for novel genes that specify the dorsal-ventral axis of the retina. By screening for mutants with altered expression of D-V markers, I identified a novel gene, bigtop, required for dorsal-ventral retinal patterning, eye development, and retinotectal projections. This mutation was mapped to a four-megabase region on chromosome two. My studies addressed the following question: how is the retina patterned early during development in order to specify retinal ganglion cells with positional fate? Altogether, my studies advanced the field of D-V retinal patterning by identifying an extraocular dorsal retinal initiation signal, uncovering the role of bmp2b in dorsal retinal initiation, and identifying a novel mutant necessary for D-V patterning

The genetic and environmental basis for CHC biosynthesis in Drosophila

Cuticular hydrocarbons (CHCs) are produced by insects and primarily used to prevent desiccation. In Drosophila, certain compounds have secondary roles as infochemicals that may act during courtship to influence mate choice. Certain CHCs may stimulate courtship with heterospecifics or act to repel conspecifics. The CHC profile produced by an individual is the result of the interaction between its genetic background and the environment, though the genes that underlie species differences in CHC production and how the environment can modulate the abundance of individual compounds within a species is not well known. Here, candidate gene CG5946 was found to be involved in species differences in the production of 7,11-heptacosadiene and 7-tricosene in hybrids between D. melanogaster and D. simulans. In addition, diet, but not microbial content, was found to influence the proportion of long-chain CHCs produced by D. melanogaster. This study provides insight into the factors influencing CHC production in Drosophila

Data integration in the era of omics: current and future challenges

To integrate heterogeneous and large omics data constitutes not only a conceptual challenge but a practical hurdle in the daily analysis of omics data. With the rise of novel omics technologies and through large-scale consortia projects, biological systems are being further investigated at an unprecedented scale generating heterogeneous and often large data sets. These data-sets encourage researchers to develop novel data integration methodologies. In this introduction we review the definition and characterize current efforts on data integration in the life sciences. We have used a web-survey to assess current research projects on data-integration to tap into the views, needs and challenges as currently perceived by parts of the research community

Discovering meaning from biological sequences: focus on predicting misannotated proteins, binding patterns, and G4-quadruplex secondary

Proteins are the principal catalytic agents, structural elements, signal transmitters, transporters, and molecular machines in cells. Experimental determination of protein function is expensive in time and resources compared to computational methods. Hence, assigning proteins function, predicting protein binding patterns, and understanding protein regulation are important problems in functional genomics and key challenges in bioinformatics. This dissertation comprises of three studies. In the first two papers, we apply machine-learning methods to (1) identify misannotated sequences and (2) predict the binding patterns of proteins. The third paper is (3) a genome-wide analysis of G4-quadruplex sequences in the maize genome. The first two papers are based on two-stage classification methods. The first stage uses machine-learning approaches that combine composition-based and sequence-based features. We use either a decision trees (HDTree) or support vector machines (SVM) as second-stage classifiers and show that classification performance reaches or outperforms more computationally expensive approaches. For study (1) our method identified potential misannotated sequences within a well-characterized set of proteins in a popular bioinformatics database. We identified misannotated proteins and show the proteins have contradicting AmiGO and UniProt annotations. For study (2), we developed a three-phase approach: Phase I classifies whether a protein binds with another protein. Phase II determines whether a protein-binding protein is a hub. Phase III classifies hub proteins based on the number of binding sites and the number of concurrent binding partners. For study (3), we carried out a computational genome-wide screen to identify non-telomeric G4-quadruplex (G4Q) elements in maize to explore their potential role in gene regulation for flowering plants. Analysis of G4Q-containing genes uncovered a striking tendency for their enrichment in genes of networks and pathways associated with electron transport, sugar degradation, and hypoxia responsiveness. The maize G4Q elements may play a previously unrecognized role in coordinating global regulation of gene expression in response to hypoxia to control carbohydrate metabolism for anaerobic metabolism. We demonstrated that our three studies have the ability to predict and provide new insights in classifying misannotated proteins, understanding protein binding patterns, and identifying a potentially new model for gene regulation

Measures for interoperability of phenotypic data: minimum information requirements and formatting

BackgroundPlant phenotypic data shrouds a wealth of information which, when accurately analysed and linked to other data types, brings to light the knowledge about the mechanisms of life. As phenotyping is a field of research comprising manifold, diverse and time-consuming experiments, the findings can be fostered by reusing and combining existing datasets. Their correct interpretation, and thus replicability, comparability and interoperability, is possible provided that the collected observations are equipped with an adequate set of metadata. So far there have been no common standards governing phenotypic data description, which hampered data exchange and reuse.ResultsIn this paper we propose the guidelines for proper handling of the information about plant phenotyping experiments, in terms of both the recommended content of the description and its formatting. We provide a document called “Minimum Information About a Plant Phenotyping Experiment”, which specifies what information about each experiment should be given, and a Phenotyping Configuration for the ISA-Tab format, which allows to practically organise this information within a dataset. We provide examples of ISA-Tab-formatted phenotypic data, and a general description of a few systems where the recommendations have been implemented.ConclusionsAcceptance of the rules described in this paper by the plant phenotyping community will help to achieve findable, accessible, interoperable and reusable data