66 research outputs found

    WikiPathways: building research communities on biological pathways.

    Get PDF
    Here, we describe the development of WikiPathways (http://www.wikipathways.org), a public wiki for pathway curation, since it was first published in 2008. New features are discussed, as well as developments in the community of contributors. New features include a zoomable pathway viewer, support for pathway ontology annotations, the ability to mark pathways as private for a limited time and the availability of stable hyperlinks to pathways and the elements therein. WikiPathways content is freely available in a variety of formats such as the BioPAX standard, and the content is increasingly adopted by external databases and tools, including Wikipedia. A recent development is the use of WikiPathways as a staging ground for centrally curated databases such as Reactome. WikiPathways is seeing steady growth in the number of users, page views and edits for each pathway. To assess whether the community curation experiment can be considered successful, here we analyze the relation between use and contribution, which gives results in line with other wiki projects. The novel use of pathway pages as supplementary material to publications, as well as the addition of tailored content for research domains, is expected to stimulate growth further

    BridgeDb: standardized access to gene, protein and metabolite identifier mapping services

    Get PDF
    Many interesting problems in bioinformatics require integration of data from various sources. For example when combining microarray data with a pathway database, or merging co-citation networks with protein-protein interaction networks. Invariably this leads to an identifier mapping problem, where different datasets are annotated with identifiers that are related, but originate from different databases.

Solutions for the identifier mapping problem exist, such as Biomart, Synergizer, Cronos, PICR, HMS and many more. This creates an opportunity for bioinformatics tool developers. Tools can be made to flexibly support multiple mapping services or mapping services could be combined to get broader coverage. This approach requires an interface layer between tools and mapping services. BridgeDb provides such an interface layer, in the form of both a Java and REST API.

Because of the standardized interface layer, BridgeDb is not tied to a specific source of mapping information. You can switch easily between flat files, relational databases and several different web services. Mapping services can be combined to support multi-omics experiments or to integrate custom microarray annotations. BridgeDb isn't just yet another mapping service: it tries to build further on existing work, and integrate multiple partial solutions. The framework is intended for customization and adaptation to any identifier mapping service. 

BridgeDb makes it easy to add an important capability to existing tools. BridgeDb has already been integrated into several popular bioinformatics applications, such as Cytoscape, WikiPathways, PathVisio, Vanted and Taverna. To encourage tool developers to start using BridgeDb, we've created code examples, online documentation, and a mailinglist to ask questions. 

We believe that, to meet the challenges that are encountered in bioinformatics today, the software development process should follow a few essential principles: user friendliness, code reuse, modularity and open source. BridgeDb adheres to these principles, and can serve as a useful model for others to follow. BridgeDb can function to increase user-friendliness of graphical applications. It re-uses work from other projects such as BioMart and MIRIAM. BridgeDb consists of several small modules, integrated through a common interface (API). Components of BridgeDb can be left out or replaced, for maximum flexibility. BridgeDb was open source from the very beginning of the project. The philosophy of open source is closely aligned to academic values, of building on top of the work of giants. 

Many interesting problems in bioinformatics require integration of data from various sources. For example when combining microarray data with a pathway database, or merging co-citation networks with protein-protein interaction networks. Invariably this leads to an identifier mapping problem, where different datasets are annotated with identifiers that are related, but originate from different databases.

Solutions for the identifier mapping problem exist, such as Biomart, Synergizer, Cronos, PICR, HMS and many more. This creates an opportunity for bioinformatics tool developers. Tools can be made to flexibly support multiple mapping services or mapping services could be combined to get broader coverage. This approach requires an interface layer between tools and mapping services. BridgeDb provides such an interface layer, in the form of both a Java and REST API.

Because of the standardized interface layer, BridgeDb is not tied to a specific source of mapping information. You can switch easily between flat files, relational databases and several different web services. Mapping services can be combined to support multi-omics experiments or to integrate custom microarray annotations. BridgeDb isn't just yet another mapping service: it tries to build further on existing work, and integrate multiple partial solutions. The framework is intended for customization and adaptation to any identifier mapping service. 

BridgeDb makes it easy to add an important capability to existing tools. BridgeDb has already been integrated into several popular bioinformatics applications, such as Cytoscape, WikiPathways, PathVisio, Vanted and Taverna. To encourage tool developers to start using BridgeDb, we've created code examples, online documentation, and a mailinglist to ask questions. 

We believe that, to meet the challenges that are encountered in bioinformatics today, the software development process should follow a few essential principles: user friendliness, code reuse, modularity and open source. BridgeDb adheres to these principles, and can serve as a useful model for others to follow. BridgeDb can function to increase user-friendliness of graphical applications. It re-uses work from other projects such as BioMart and MIRIAM. BridgeDb consists of several small modules, integrated through a common interface (API). Components of BridgeDb can be left out or replaced, for maximum flexibility. BridgeDb was open source from the very beginning of the project. The philosophy of open source is closely aligned to academic values, of building on top of the work of giants. 

The BridgeDb library is available at "http://www.bridgedb.org":http://www.bridgedb.org.
A paper about BridgeDb was published in BMC _Bioinformatics_, 2010 Jan 4;11(1):5.

BridgeDb blog: "http://www.helixsoft.nl/blog/?tag=bridgedb":http://www.helixsoft.nl/blog/?tag=bridged

    WikiPathways: Pathway Editing for the People

    Get PDF
    WikiPathways provides a collaborative platform for creating, updating, and sharing pathway diagrams and serves as an example of content curation by the biology community

    GenMAPP 2: New features and resources for pathway analysis

    Get PDF
    BACKGROUND: Microarray technologies have evolved rapidly, enabling biologists to quantify genome-wide levels of gene expression, alternative splicing, and sequence variations for a variety of species. Analyzing and displaying these data present a significant challenge. Pathway-based approaches for analyzing microarray data have proven useful for presenting data and for generating testable hypotheses. RESULTS: To address the growing needs of the microarray community we have released version 2 of Gene Map Annotator and Pathway Profiler (GenMAPP), a new GenMAPP database schema, and integrated resources for pathway analysis. We have redesigned the GenMAPP database to support multiple gene annotations and species as well as custom species database creation for a potentially unlimited number of species. We have expanded our pathway resources by utilizing homology information to translate pathway content between species and extending existing pathways with data derived from conserved protein interactions and coexpression. We have implemented a new mode of data visualization to support analysis of complex data, including time-course, single nucleotide polymorphism (SNP), and splicing. GenMAPP version 2 also offers innovative ways to display and share data by incorporating HTML export of analyses for entire sets of pathways as organized web pages. CONCLUSION: GenMAPP version 2 provides a means to rapidly interrogate complex experimental data for pathway-level changes in a diverse range of organisms

    BioThings Explorer: a query engine for a federated knowledge graph of biomedical APIs

    Full text link
    Knowledge graphs are an increasingly common data structure for representing biomedical information. These knowledge graphs can easily represent heterogeneous types of information, and many algorithms and tools exist for querying and analyzing graphs. Biomedical knowledge graphs have been used in a variety of applications, including drug repurposing, identification of drug targets, prediction of drug side effects, and clinical decision support. Typically, knowledge graphs are constructed by centralization and integration of data from multiple disparate sources. Here, we describe BioThings Explorer, an application that can query a virtual, federated knowledge graph derived from the aggregated information in a network of biomedical web services. BioThings Explorer leverages semantically precise annotations of the inputs and outputs for each resource, and automates the chaining of web service calls to execute multi-step graph queries. Because there is no large, centralized knowledge graph to maintain, BioThing Explorer is distributed as a lightweight application that dynamically retrieves information at query time. More information can be found at https://explorer.biothings.io, and code is available at https://github.com/biothings/biothings_explorer

    Mining Biological Pathways Using WikiPathways Web Services

    Get PDF
    WikiPathways is a platform for creating, updating, and sharing biological pathways [1]. Pathways can be edited and downloaded using the wiki-style website. Here we present a SOAP web service that provides programmatic access to WikiPathways that is complementary to the website. We describe the functionality that this web service offers and discuss several use cases in detail. Exposing WikiPathways through a web service opens up new ways of utilizing pathway information and assisting the community curation process

    The BridgeDb framework: standardized access to gene, protein and metabolite identifier mapping services

    Get PDF
    BACKGROUND: Many complementary solutions are available for the identifier mapping problem. This creates an opportunity for bioinformatics tool developers. Tools can be made to flexibly support multiple mapping services or mapping services could be combined to get broader coverage. This approach requires an interface layer between tools and mapping services. RESULTS: Here we present BridgeDb, a software framework for gene, protein and metabolite identifier mapping. This framework provides a standardized interface layer through which bioinformatics tools can be connected to different identifier mapping services. This approach makes it easier for tool developers to support identifier mapping. Mapping services can be combined or merged to support multi-omics experiments or to integrate custom microarray annotations. BridgeDb provides its own ready-to-go mapping services, both in webservice and local database forms. However, the framework is intended for customization and adaptation to any identifier mapping service. BridgeDb has already been integrated into several bioinformatics applications. CONCLUSION: By uncoupling bioinformatics tools from mapping services, BridgeDb improves capability and flexibility of those tools. All described software is open source and available at http://www.bridgedb.org

    Modeling Insertional Mutagenesis Using Gene Length and Expression in Murine Embryonic Stem Cells

    Get PDF
    Background. High-throughput mutagenesis of the mammalian genome is a powerful means to facilitate analysis of gene function. Gene trapping in embryonic stem cells (ESCs) is the most widely used form of insertional mutagenesis in mammals. However, the rules governing its efficiency are not fully understood, and the effects of vector design on the likelihood of genetrapping events have not been tested on a genome-wide scale. Methodology/Principal Findings. In this study, we used public gene-trap data to model gene-trap likelihood. Using the association of gene length and gene expression with gene-trap likelihood, we constructed spline-based regression models that characterize which genes are susceptible and which genes are resistant to gene-trapping techniques. We report results for three classes of gene-trap vectors, showing that both length and expression are significant determinants of trap likelihood for all vectors. Using our models, we also quantitatively identifie

    Alternative Splicing in the Differentiation of Human Embryonic Stem Cells into Cardiac Precursors

    Get PDF
    The role of alternative splicing in self-renewal, pluripotency and tissue lineage specification of human embryonic stem cells (hESCs) is largely unknown. To better define these regulatory cues, we modified the H9 hESC line to allow selection of pluripotent hESCs by neomycin resistance and cardiac progenitors by puromycin resistance. Exon-level microarray expression data from undifferentiated hESCs and cardiac and neural precursors were used to identify splice isoforms with cardiac-restricted or common cardiac/neural differentiation expression patterns. Splice events for these groups corresponded to the pathways of cytoskeletal remodeling, RNA splicing, muscle specification, and cell cycle checkpoint control as well as genes with serine/threonine kinase and helicase activity. Using a new program named AltAnalyze (http://www.AltAnalyze.org), we identified novel changes in protein domain and microRNA binding site architecture that were predicted to affect protein function and expression. These included an enrichment of splice isoforms that oppose cell-cycle arrest in hESCs and that promote calcium signaling and cardiac development in cardiac precursors. By combining genome-wide predictions of alternative splicing with new functional annotations, our data suggest potential mechanisms that may influence lineage commitment and hESC maintenance at the level of specific splice isoforms and microRNA regulation
    • …
    corecore