Integrating biological data--the Distributed Annotation System

BioViz Connect: Web Application Linking CyVerse Cloud Resources to Genomic Visualization in the Integrated Genome Browser

Genomics researchers do better work when they can interactively explore and visualize data. Due to the vast size of experimental datasets, researchers are increasingly using powerful, cloud-based systems to process and analyze data. These remote systems, called science gateways, offer user-friendly, Web-based access to high performance computing and storage resources, but typically lack interactive visualization capability. In this paper, we present BioViz Connect, a middleware Web application that links CyVerse science gateway resources to the Integrated Genome Browser (IGB), a highly interactive native application implemented in Java that runs on the user's personal computer. Using BioViz Connect, users can 1) stream data from the CyVerse data store into IGB for visualization, 2) improve the IGB user experience for themselves and others by adding IGB specific metadata to CyVerse data files, including genome version and track appearance, and 3) run compute-intensive visual analytics functions on CyVerse infrastructure to create new datasets for visualization in IGB or other applications. To demonstrate how BioViz Connect facilitates interactive data visualization, we describe an example RNA-Seq data analysis investigating how heat and desiccation stresses affect gene expression in the model plant Arabidopsis thaliana. The RNA-Seq use case illustrates how interactive visualization with IGB can help a user identify problematic experimental samples, sanity-check results using a positive control, and create new data files for interactive visualization in IGB (or other tools) using a Docker image deployed to CyVerse via the Terrain API. Lastly, we discuss limitations of the technologies used and suggest opportunities for future work. BioViz Connect is available from https://bioviz.org.

Data Integration Challenges for Machine Learning in Precision Medicine

A main goal of Precision Medicine is that of incorporating and integrating the vast corpora on different databases about the molecular and environmental origins of disease, into analytic frameworks, allowing the development of individualized, context-dependent diagnostics, and therapeutic approaches. In this regard, artificial intelligence and machine learning approaches can be used to build analytical models of complex disease aimed at prediction of personalized health conditions and outcomes. Such models must handle the wide heterogeneity of individuals in both their genetic predisposition and their social and environmental determinants. Computational approaches to medicine need to be able to efficiently manage, visualize and integrate, large datasets combining structure, and unstructured formats. This needs to be done while constrained by different levels of confidentiality, ideally doing so within a unified analytical architecture. Efficient data integration and management is key to the successful application of computational intelligence approaches to medicine. A number of challenges arise in the design of successful designs to medical data analytics under currently demanding conditions of performance in personalized medicine, while also subject to time, computational power, and bioethical constraints. Here, we will review some of these constraints and discuss possible avenues to overcome current challenges.

Isomorphic semantic mapping of variant call format (VCF2RDF)

Summary

The move of computational genomics workflows to Cloud Computing platforms is associated with a new level of integration and interoperability that challenges existing data representation formats. The Variant Calling Format (VCF) is in a particularly sensitive position in that regard, with both clinical and consumer-facing analysis tools relying on this self-contained description of genomic variation in Next Generation Sequencing (NGS) results. In this report we identify an isomorphic map between VCF and the reference Resource Description Framework. RDF is advanced by the World Wide Web Consortium (W3C) to enable representations of linked data that are both distributed and discoverable. The resulting ability to decompose VCF reports of genomic variation without loss of context addresses the need to modularize and govern NGS pipelines for Precision Medicine. Specifically, it provides the flexibility (i.e. the indexing) needed to support the wide variety of clinical scenarios and patient-facing governance where only part of the VCF data is fitting.

Availability and Implementation

Software libraries with a claim to be both domain-facing and consumer-facing have to pass the test of portability across the variety of devices that those consumers in fact adopt. That is, ideally the implementation should itself take place within the space defined by web technologies. Consequently, the isomorphic mapping function was implemented in JavaScript, and was tested in a variety of environments and devices, client and server side alike. These range from web browsers in mobile phones to the most popular micro service platform, NodeJS. The code is publicly available at https://github.com/ibl/VCFr , with a live deployment at: http://ibl.github.io/VCFr/ .

Contact

jonas.almeida@stonybrookmedicine.edu.

Phenotype databases for genetic screens in human cells

Genetic screens are powerful tools to identify components that make up biological systems. Perturbations introduced by methods such as RNA interference (RNAi) or CRISPR/Cas9-mediated genome editing lead to biological phenotypes that can be examined to understand the molecular function of genes in the cell. Over the years, many of such experiments have been conducted providing a wealth of knowledge about genotype-to-phenotype relationships. These data are a rich source of information and it is in a common interest to make them available in a simplified and integrated format. Thus, an important challenge is that genetic screening data can be stored in databases in standardized ways, allowing users to gain new biological insights through data mining and integrated analyses. Here, we provide an overview of available phenotype databases for human cells. We review in detail two databases for high-throughput screens, GenomeRNAi and GenomeCRISPR, and describe how these resources are integrated into the German Network for Bioinformatics Infrastructure de.NBI as part of the European infrastructure for life-science information ELIXIR.

Genome and network visualization facilitates the analyses of the effects of drugs and mutations on protein-protein and drug-protein networks

BACKGROUND

Biologists generally interrogate genomics data using web-based genome browsers that have limited analytical potential. New generation genome browsers such as the Integrated Genome Browser (IGB) have largely overcome this limitation and permit customized analyses to be implemented using plugins. We illustrate the use of a plugin for IGB that exploits advanced visualization techniques to integrate the analysis of genomics data with network and structural approaches.

RESULTS

We show how visualization technologies that combine both genomics and network biology can facilitate the selection of the key amino acid contacts from protein-protein and protein-drug interactions. Starting from the MDM2-P53 interaction, which is a high-value target for cancer therapy, and Nutlin, the parent small molecule of an MDM2 antagonist that is currently in clinical trials, we show that this method can be generalized to analyze how drugs and mutations can interfere with both protein-protein and drug-protein networks. We illustrate this point by two additional use-cases exploring the molecular basis of tamoxifen side effects and of drug resistance in chronic myeloid leukemia patients.

CONCLUSIONS

Combined network and structure biology approaches provide key insights into both the genetic and the edgetic roles of variants in diseases. 3D interactomes facilitate the identification of disease-relevant interactions that can then be specifically targeted by drugs. Recent advances in molecular interaction and structure visualization tools have greatly simplified the mapping of mutated residues to molecular interaction interfaces. Such approaches can now also be integrated with genome visualization tools to enable comparative analyses of interaction contacts.

The EBI Search engine: providing search and retrieval functionality for biological data from EMBL-EBI

The European Bioinformatics Institute (EMBL-EBI-https://www.ebi.ac.uk) provides free and unrestricted access to data across all major areas of biology and biomedicine. Searching and extracting knowledge across these domains requires a fast and scalable solution that addresses the requirements of domain experts as well as casual users. We present the EBI Search engine, referred to here as 'EBI Search', an easy-to-use fast text search and indexing system with powerful data navigation and retrieval capabilities. API integration provides access to analytical tools, allowing users to further investigate the results of their search. The interconnectivity that exists between data resources at EMBL-EBI provides easy, quick and precise navigation and a better understanding of the relationship between different data types including sequences, genes, gene products, proteins, protein domains, protein families, enzymes and macromolecular structures, together with relevant life science literature.

Personalized Oncology Suite: integrating next-generation sequencing data and whole-slide bioimages

Background

Cancer immunotherapy has recently entered a remarkable renaissance phase with the approval of several agents for treatment. Cancer treatment platforms have demonstrated profound tumor regressions including complete cure in patients with metastatic cancer. Moreover, technological advances in next-generation sequencing (NGS) as well as the development of devices for scanning whole-slide bioimages from tissue sections and image analysis software for quantitation of tumor-infiltrating lymphocytes (TILs) allow, for the first time, the development of personalized cancer immunotherapies that target patient specific mutations. However, there is currently no bioinformatics solution that supports the integration of these heterogeneous datasets.

Results

We have developed a bioinformatics platform – Personalized Oncology Suite (POS) – that integrates clinical data, NGS data and whole-slide bioimages from tissue sections. POS is a web-based platform that is scalable, flexible and expandable. The underlying database is based on a data warehouse schema, which is used to integrate information from different sources. POS stores clinical data, genomic data (SNPs and INDELs identified from NGS analysis), and scanned whole-slide images. It features a genome browser as well as access to several instances of the bioimage management application Bisque. POS provides different visualization techniques and offers sophisticated upload and download possibilities. The modular architecture of POS allows the community to easily modify and extend the application.

Conclusions

The web-based integration of clinical, NGS, and imaging data represents a valuable resource for clinical researchers and future application in medical oncology. POS can be used not only in the context of cancer immunology but also in other studies in which NGS data and images of tissue sections are generated. The application is open-source and can be downloaded at http://www.icbi.at/POS.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-306) contains supplementary material, which is available to authorized users.

The Ensembl REST API: Ensembl Data for Any Language

MOTIVATION

We present a Web service to access Ensembl data using Representational State Transfer (REST). The Ensembl REST server enables the easy retrieval of a wide range of Ensembl data by most programming languages, using standard formats such as JSON and FASTA while minimizing client work. We also introduce bindings to the popular Ensembl Variant Effect Predictor tool permitting large-scale programmatic variant analysis independent of any specific programming language.

AVAILABILITY AND IMPLEMENTATION

The Ensembl REST API can be accessed at http://rest.ensembl.org and source code is freely available under an Apache 2.0 license from http://github.com/Ensembl/ensembl-rest.

FISH Oracle 2: a web server for integrative visualization of genomic data in cancer research

Background

A comprehensive view on all relevant genomic data is instrumental for understanding the complex patterns of molecular alterations typically found in cancer cells. One of the most effective ways to rapidly obtain an overview of genomic alterations in large amounts of genomic data is the integrative visualization of genomic events.

Results

We developed FISH Oracle 2, a web server for the interactive visualization of different kinds of downstream processed genomics data typically available in cancer research. A powerful search interface and a fast visualization engine provide a highly interactive visualization for such data. High quality image export enables the life scientist to easily communicate their results. A comprehensive data administration allows to keep track of the available data sets. We applied FISH Oracle 2 to published data and found evidence that, in colorectal cancer cells, the gene TTC28 may be inactivated in two different ways, a fact that has not been published before.

Conclusions

The interactive nature of FISH Oracle 2 and the possibility to store, select and visualize large amounts of downstream processed data support life scientists in generating hypotheses. The export of high quality images supports explanatory data visualization, simplifying the communication of new biological findings. A FISH Oracle 2 demo server and the software is available at http://www.zbh.uni-hamburg.de/fishoracle.

openSNP--a crowdsourced web resource for personal genomics

Genome-Wide Association Studies are widely used to correlate phenotypic traits with genetic variants. These studies usually compare the genetic variation between two groups to single out certain Single Nucleotide Polymorphisms (SNPs) that are linked to a phenotypic variation in one of the groups. However, it is necessary to have a large enough sample size to find statistically significant correlations. Direct-To-Consumer (DTC) genetic testing can supply additional data: DTC-companies offer the analysis of a large amount of SNPs for an individual at low cost without the need to consult a physician or geneticist. Over 100,000 people have already been genotyped through Direct-To-Consumer genetic testing companies. However, this data is not public for a variety of reasons and thus cannot be used in research. It seems reasonable to create a central open data repository for such data. Here we present the web platform openSNP, an open database which allows participants of Direct-To-Consumer genetic testing to publish their genetic data at no cost along with phenotypic information. Through this crowdsourced effort of collecting genetic and phenotypic information, openSNP has become a resource for a wide area of studies, including Genome-Wide Association Studies. openSNP is hosted at http://www.opensnp.org, and the code is released under MIT-license at http://github.com/gedankenstuecke/snpr.

FeatureViewer, a BioJS component for visualization of position-based annotations in protein sequences

SUMMARY

FeatureViewer is a BioJS component that lays out, maps, orients, and renders position-based annotations for protein sequences. This component is highly flexible and customizable, allowing the presentation of annotations by rows, all centered, or distributed in non-overlapping tracks. It uses either lines or shapes for sites and rectangles for regions. The result is a powerful visualization tool that can be easily integrated into web applications as well as documents as it provides an export-to-image functionality.

AVAILABILITY

https://github.com/biojs/biojs/blob/master/src/main/javascript/Biojs.FeatureViewer.js; http://dx.doi.org/10.5281/zenodo.7719.

Integrated Bio-Search: challenges and trends for the integration, search and comprehensive processing of biological information

Many efforts exist to design and implement approaches and tools for data capture, integration and analysis in the life sciences. Challenges are not only the heterogeneity, size and distribution of information sources, but also the danger of producing too many solutions for the same problem. Methodological, technological, infrastructural and social aspects appear to be essential for the development of a new generation of best practices and tools. In this paper, we analyse and discuss these aspects from different perspectives, by extending some of the ideas that arose during the NETTAB 2012 Workshop, making reference especially to the European context. First, relevance of using data and software models for the management and analysis of biological data is stressed. Second, some of the most relevant community achievements of the recent years, which should be taken as a starting point for future efforts in this research domain, are presented. Third, some of the main outstanding issues, challenges and trends are analysed. The challenges related to the tendency to fund and create large scale international research infrastructures and public-private partnerships in order to address the complex challenges of data intensive science are especially discussed. The needs and opportunities of Genomic Computing (the integration, search and display of genomic information at a very specific level, e.g. at the level of a single DNA region) are then considered. In the current data and network-driven era, social aspects can become crucial bottlenecks. How these may best be tackled to unleash the technical abilities for effective data integration and validation efforts is then discussed. Especially the apparent lack of incentives for already overwhelmed researchers appears to be a limitation for sharing information and knowledge with other scientists. We point out as well how the bioinformatics market is growing at an unprecedented speed due to the impact that new powerful in silico analysis promises to have on better diagnosis, prognosis, drug discovery and treatment, towards personalized medicine. An open business model for bioinformatics, which appears to be able to reduce undue duplication of efforts and support the increased reuse of valuable data sets, tools and platforms, is finally discussed.

Gene-centric content management system

The Human Proteome Project (HPP) was started two years ago and the international consortia have elaborated a number of informational resources to harbor the HPP data. Selected informational resources are currently used to elaborate the HPP baseline metrics, which were introduced to estimate future contribution of HPP to the knowledge domain. We developed a Web-based tool Gene-centric Content Management System (GenoCMS) for comparing public resources to proprietary results by using the representation of proteins as color-coded catalog. Within our CMS, the features of protein-coding genes are uploaded from the public domain and then appended by additional features derived from original experimental workflows. We describe the heat-map/traffic light representation of our proteomic experiments as the background of data taken from NeXtProt, MS/MS repositories, the Human Protein Atlas and the RNAseqAtlas. The system presented at www.kb18.ru comprises a collaborative knowledge base for annotating the gene sets and disseminating these annotations through the Web. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan.

On an infrastructure to support sharing and aggregating pre- and post-publication systems biology research data

The move towards in silico experimentation has resulted in the use of computational models, in addition to traditional experimental models, to generate the raw data that is analysed and published as research findings. This change requires new methods to be introduced to facilitate independent validation of the underlying models and the reported results. The promotion of co-operative research has the potential to help to both validate results and explore wider problem areas. In this paper we leverage and extend two existing software frameworks to develop an infrastructure that has the potential to both promote the sharing of data between researchers pre-publication and enable access to the data for interested parties post-publication. The pre-publication sharing of data would enable larger problem spaces to be explored by distributed research groups; enabling access to the data post-publication would allow reviewers and the wider community to independently verify the published results which would, in the longer term, help to increase confidence in published results. The framework is used to perform reproducible and numerically validated individual-based computational experiments into the onset of colorectal cancer. Existing results are verified and new insights into the top-down versus bottom-up hypothesis of colorectal crypt invasion are given.

The Enzyme Portal: a case study in applying user-centred design methods in bioinformatics

User-centred design (UCD) is a type of user interface design in which the needs and desires of users are taken into account at each stage of the design process for a service or product; often for software applications and websites. Its goal is to facilitate the design of software that is both useful and easy to use. To achieve this, you must characterise users' requirements, design suitable interactions to meet their needs, and test your designs using prototypes and real life scenarios.For bioinformatics, there is little practical information available regarding how to carry out UCD in practice. To address this we describe a complete, multi-stage UCD process used for creating a new bioinformatics resource for integrating enzyme information, called the Enzyme Portal (http://www.ebi.ac.uk/enzymeportal). This freely-available service mines and displays data about proteins with enzymatic activity from public repositories via a single search, and includes biochemical reactions, biological pathways, small molecule chemistry, disease information, 3D protein structures and relevant scientific literature.We employed several UCD techniques, including: persona development, interviews, 'canvas sort' card sorting, user workflows, usability testing and others. Our hope is that this case study will motivate the reader to apply similar UCD approaches to their own software design for bioinformatics. Indeed, we found the benefits included more effective decision-making for design ideas and technologies; enhanced team-working and communication; cost effectiveness; and ultimately a service that more closely meets the needs of our target audience.

Teaching the fundamentals of biological data integration using classroom games

This article aims to introduce the nature of data integration to life scientists. Generally, the subject of data integration is not discussed outside the field of computational science and is not covered in any detail, or even neglected, when teaching/training trainees. End users (hereby defined as wet-lab trainees, clinicians, lab researchers) will mostly interact with bioinformatics resources and tools through web interfaces that mask the user from the data integration processes. However, the lack of formal training or acquaintance with even simple database concepts and terminology often results in a real obstacle to the full comprehension of the resources and tools the end users wish to access. Understanding how data integration works is fundamental to empowering trainees to see the limitations as well as the possibilities when exploring, retrieving, and analysing biological data from databases. Here we introduce a game-based learning activity for training/teaching the topic of data integration that trainers/educators can adopt and adapt for their classroom. In particular we provide an example using DAS (Distributed Annotation Systems) as a method for data integration.

The Functional Genomics Network in the evolution of biological text mining over the past decade

Different programs of The European Science Foundation (ESF) have contributed significantly to connect researchers in Europe and beyond through several initiatives. This support was particularly relevant for the development of the areas related with extracting information from papers (text-mining) because it supported the field in its early phases long before it was recognized by the community. We review the historical development of text mining research and how it was introduced in bioinformatics. Specific applications in (functional) genomics are described like it's integration in genome annotation pipelines and the support to the analysis of high-throughput genomics experimental data, and we highlight the activities of evaluation of methods and benchmarking for which the ESF programme support was instrumental.

GenomeRNAi: a database for cell-based and in vivo RNAi phenotypes, 2013 update

RNA interference (RNAi) represents a powerful method to systematically study loss-of-function phenotypes on a large scale with a wide variety of biological assays, constituting a rich source for the assignment of gene function. The GenomeRNAi database (http://www.genomernai.org) makes available RNAi phenotype data extracted from the literature for human and Drosophila. It also provides RNAi reagent information, along with an assessment as to their efficiency and specificity. This manuscript describes an update of the database previously featured in the NAR Database Issue. The new version has undergone a complete re-design of the user interface, providing an intuitive, flexible framework for additional functionalities. Screen information and gene-reagent-phenotype associations are now available for download. The integration with other resources has been improved by allowing in-links via GenomeRNAi screen IDs, or external gene or reagent identifiers. A distributed annotation system (DAS) server enables the visualization of the phenotypes and reagents in the context of a genome browser. We have added a page listing ‘frequent hitters’, i.e. genes that show a phenotype in many screens, which might guide on-going RNAi studies. Structured annotation guidelines have been established to facilitate consistent curation, and a submission template for direct submission by data producers is available for download.

MyDas, an extensible Java DAS server

A large number of diverse, complex, and distributed data resources are currently available in the Bioinformatics domain. The pace of discovery and the diversity of information means that centralised reference databases like UniProt and Ensembl cannot integrate all potentially relevant information sources. From a user perspective however, centralised access to all relevant information concerning a specific query is essential. The Distributed Annotation System (DAS) defines a communication protocol to exchange annotations on genomic and protein sequences; this standardisation enables clients to retrieve data from a myriad of sources, thus offering centralised access to end-users.

We introduce MyDas, a web server that facilitates the publishing of biological annotations according to the DAS specification. It deals with the common functionality requirements of making data available, while also providing an extension mechanism in order to implement the specifics of data store interaction. MyDas allows the user to define where the required information is located along with its structure, and is then responsible for the communication protocol details.

VarioML framework for comprehensive variation data representation and exchange

BACKGROUND

Sharing of data about variation and the associated phenotypes is a critical need, yet variant information can be arbitrarily complex, making a single standard vocabulary elusive and re-formatting difficult. Complex standards have proven too time-consuming to implement.

RESULTS

The GEN2PHEN project addressed these difficulties by developing a comprehensive data model for capturing biomedical observations, Observ-OM, and building the VarioML format around it. VarioML pairs a simplified open specification for describing variants, with a toolkit for adapting the specification into one's own research workflow. Straightforward variant data can be captured, federated, and exchanged with no overhead; more complex data can be described, without loss of compatibility. The open specification enables push-button submission to gene variant databases (LSDBs) e.g., the Leiden Open Variation Database, using the Cafe Variome data publishing service, while VarioML bidirectionally transforms data between XML and web-application code formats, opening up new possibilities for open source web applications building on shared data. A Java implementation toolkit makes VarioML easily integrated into biomedical applications. VarioML is designed primarily for LSDB data submission and transfer scenarios, but can also be used as a standard variation data format for JSON and XML document databases and user interface components.

CONCLUSIONS

VarioML is a set of tools and practices improving the availability, quality, and comprehensibility of human variation information. It enables researchers, diagnostic laboratories, and clinics to share that information with ease, clarity, and without ambiguity.

A web-based bioinformatics interface applied to the GENOSOJA Project: Databases and pipelines

The Genosoja consortium is an initiative to integrate different omics research approaches carried out in Brazil. Basically, the aim of the project is to improve the plant by identifying genes involved in responses against stresses that affect domestic production, like drought stress and Asian Rust fungal disease. To do so, the project generated several types of sequence data using different methodologies, most of them sequenced by next generation sequencers. The initial stage of the project is highly dependent on bioinformatics analysis, providing suitable tools and integrated databases. In this work, we describe the main features of the Genosoja web database, including the pipelines to analyze some kinds of data (ESTs, SuperSAGE, microRNAs, subtractive cDNA libraries), as well as web interfaces to access information about soybean gene annotation and expression.

Taking the next step: building an Arabidopsis information portal

The Arabidopsis information portal (AIP), a resource expected to provide access to all community data and combine outputs into a single user-friendly interface, has emerged from community discussions over the last 23 months. These discussions began during two closely linked workshops in early 2010 that established the International Arabidopsis Informatics Consortium (IAIC). The design of the AIP will provide core functionality while remaining flexible to encourage multiple contributors and constant innovation. An IAIC-hosted Design Workshop in December 2011 proposed a structure for the AIP to provide a framework for the minimal components of a functional community portal while retaining flexibility to rapidly extend the resource to other species. We now invite broader participation in the AIP development process so that the resource can be implemented in a timely manner.

Relax with CouchDB--into the non-relational DBMS era of bioinformatics

With the proliferation of high-throughput technologies, genome-level data analysis has become common in molecular biology. Bioinformaticians are developing extensive resources to annotate and mine biological features from high-throughput data. The underlying database management systems for most bioinformatics software are based on a relational model. Modern non-relational databases offer an alternative that has flexibility, scalability, and a non-rigid design schema. Moreover, with an accelerated development pace, non-relational databases like CouchDB can be ideal tools to construct bioinformatics utilities. We describe CouchDB by presenting three new bioinformatics resources: (a) geneSmash, which collates data from bioinformatics resources and provides automated gene-centric annotations, (b) drugBase, a database of drug-target interactions with a web interface powered by geneSmash, and (c) HapMap-CN, which provides a web interface to query copy number variations from three SNP-chip HapMap datasets. In addition to the web sites, all three systems can be accessed programmatically via web services.

Visualizing next-generation sequencing data with JBrowse

JBrowse is a web-based genome browser, allowing many sources of data to be visualized, interpreted and navigated in a coherent visual framework. JBrowse uses efficient data structures, pre-generation of image tiles and client-side rendering to provide a fast, interactive browsing experience. Many of JBrowse's design features make it well suited for visualizing high-volume data, such as aligned next-generation sequencing reads.

The UCSC Genome Browser database: extensions and updates 2011

The University of California Santa Cruz Genome Browser (http://genome.ucsc.edu) offers online public access to a growing database of genomic sequence and annotations for a wide variety of organisms. The Browser is an integrated tool set for visualizing, comparing, analyzing and sharing both publicly available and user-generated genomic data sets. In the past year, the local database has been updated with four new species assemblies, and we anticipate another four will be released by the end of 2011. Further, a large number of annotation tracks have been either added, updated by contributors, or remapped to the latest human reference genome. Among these are new phenotype and disease annotations, UCSC genes, and a major dbSNP update, which required new visualization methods. Growing beyond the local database, this year we have introduced 'track data hubs', which allow the Genome Browser to provide access to remotely located sets of annotations. This feature is designed to significantly extend the number and variety of annotation tracks that are publicly available for visualization and analysis from within our site. We have also introduced several usability features including track search and a context-sensitive menu of options available with a right-click anywhere on the Browser's image.

VectorBase: improvements to a bioinformatics resource for invertebrate vector genomics

VectorBase (http://www.vectorbase.org) is a NIAID-supported bioinformatics resource for invertebrate vectors of human pathogens. It hosts data for nine genomes: mosquitoes (three Anopheles gambiae genomes, Aedes aegypti and Culex quinquefasciatus), tick (Ixodes scapularis), body louse (Pediculus humanus), kissing bug (Rhodnius prolixus) and tsetse fly (Glossina morsitans). Hosted data range from genomic features and expression data to population genetics and ontologies. We describe improvements and integration of new data that expand our taxonomic coverage. Releases are bi-monthly and include the delivery of preliminary data for emerging genomes. Frequent updates of the genome browser provide VectorBase users with increasing options for visualizing their own high-throughput data. One major development is a new population biology resource for storing genomic variations, insecticide resistance data and their associated metadata. It takes advantage of improved ontologies and controlled vocabularies. Combined, these new features ensure timely release of multiple types of data in the public domain while helping overcome the bottlenecks of bioinformatics and annotation by engaging with our user community.

InterPro in 2011: new developments in the family and domain prediction database

InterPro (http://www.ebi.ac.uk/interpro/) is a database that integrates diverse information about protein families, domains and functional sites, and makes it freely available to the public via Web-based interfaces and services. Central to the database are diagnostic models, known as signatures, against which protein sequences can be searched to determine their potential function. InterPro has utility in the large-scale analysis of whole genomes and meta-genomes, as well as in characterizing individual protein sequences. Herein we give an overview of new developments in the database and its associated software since 2009, including updates to database content, curation processes and Web and programmatic interfaces.

Ensembl Genomes: an integrative resource for genome-scale data from non-vertebrate species

Ensembl Genomes (http://www.ensemblgenomes.org) is an integrative resource for genome-scale data from non-vertebrate species. The project exploits and extends technology (for genome annotation, analysis and dissemination) developed in the context of the (vertebrate-focused) Ensembl project and provides a complementary set of resources for non-vertebrate species through a consistent set of programmatic and interactive interfaces. These provide access to data including reference sequence, gene models, transcriptional data, polymorphisms and comparative analysis. Since its launch in 2009, Ensembl Genomes has undergone rapid expansion, with the goal of providing coverage of all major experimental organisms, and additionally including taxonomic reference points to provide the evolutionary context in which genes can be understood. Against the backdrop of a continuing increase in genome sequencing activities in all parts of the tree of life, we seek to work, wherever possible, with the communities actively generating and using data, and are participants in a growing range of collaborations involved in the annotation and analysis of genomes.

myKaryoView: a light-weight client for visualization of genomic data

The Distributed Annotation System (DAS) is a protocol for easy sharing and integration of biological annotations. In order to visualize feature annotations in a genomic context a client is required. Here we present myKaryoView, a simple light-weight DAS tool for visualization of genomic annotation. myKaryoView has been specifically configured to help analyse data derived from personal genomics, although it can also be used as a generic genome browser visualization. Several well-known data sources are provided to facilitate comparison of known genes and normal variation regions. The navigation experience is enhanced by simultaneous rendering of different levels of detail across chromosomes. A simple interface is provided to allow searches for any SNP, gene or chromosomal region. User-defined DAS data sources may also be added when querying the system. We demonstrate myKaryoView capabilities for adding user-defined sources with a set of genetic profiles of family-related individuals downloaded directly from 23andMe. myKaryoView is a web tool for visualization of genomic data specifically designed for direct-to-consumer genomic data that uses publicly available data distributed throughout the Internet. It does not require data to be held locally and it is capable of rendering any feature as long as it conforms to DAS specifications. Configuration and addition of sources to myKaryoView can be done through the interface. Here we show a proof of principle of myKaryoView's ability to display personal genomics data with 23andMe genome data sources. The tool is available at: http://mykaryoview.com.

pubmed2ensembl: a resource for mining the biological literature on genes

BACKGROUND

The last two decades have witnessed a dramatic acceleration in the production of genomic sequence information and publication of biomedical articles. Despite the fact that genome sequence data and publications are two of the most heavily relied-upon sources of information for many biologists, very little effort has been made to systematically integrate data from genomic sequences directly with the biological literature. For a limited number of model organisms dedicated teams manually curate publications about genes; however for species with no such dedicated staff many thousands of articles are never mapped to genes or genomic regions.

METHODOLOGY/PRINCIPAL FINDINGS

To overcome the lack of integration between genomic data and biological literature, we have developed pubmed2ensembl (http://www.pubmed2ensembl.org), an extension to the BioMart system that links over 2,000,000 articles in PubMed to nearly 150,000 genes in Ensembl from 50 species. We use several sources of curated (e.g., Entrez Gene) and automatically generated (e.g., gene names extracted through text-mining on MEDLINE records) sources of gene-publication links, allowing users to filter and combine different data sources to suit their individual needs for information extraction and biological discovery. In addition to extending the Ensembl BioMart database to include published information on genes, we also implemented a scripting language for automated BioMart construction and a novel BioMart interface that allows text-based queries to be performed against PubMed and PubMed Central documents in conjunction with constraints on genomic features. Finally, we illustrate the potential of pubmed2ensembl through typical use cases that involve integrated queries across the biomedical literature and genomic data.

CONCLUSION/SIGNIFICANCE

By allowing biologists to find the relevant literature on specific genomic regions or sets of functionally related genes more easily, pubmed2ensembl offers a much-needed genome informatics inspired solution to accessing the ever-increasing biomedical literature.

Dasty3, a WEB framework for DAS

Motivation: Dasty3 is a highly interactive and extensible Web-based framework. It provides a rich Application Programming Interface upon which it is possible to develop specialized clients capable of retrieving information from DAS sources as well as from data providers not using the DAS protocol. Dasty3 provides significant improvements on previous Web-based frameworks and is implemented using the 1.6 DAS specification.

Availability: Dasty3 is an open-source tool freely available at http://www.ebi.ac.uk/dasty/ under the terms of the GNU General public license. Source and documentation can be found at http://code.google.com/p/dasty/.

Contact:hhe@ebi.ac.uk

The InterPro BioMart: federated query and web service access to the InterPro Resource

The InterPro BioMart provides users with query-optimized access to predictions of family classification, protein domains and functional sites, based on a broad spectrum of integrated computational models ('signatures') that are generated by the InterPro member databases: Gene3D, HAMAP, PANTHER, Pfam, PIRSF, PRINTS, ProDom, PROSITE, SMART, SUPERFAMILY and TIGRFAMs. These predictions are provided for all protein sequences from both the UniProt Knowledge Base and the UniParc protein sequence archive. The InterPro BioMart is supplementary to the primary InterPro web interface (http://www.ebi.ac.uk/interpro), providing a web service and the ability to build complex, custom queries that can efficiently return thousands of rows of data in a variety of formats. This article describes the information available from the InterPro BioMart and illustrates its utility with examples of how to build queries that return useful biological information. Database URL: http://www.ebi.ac.uk/interpro/biomart/martview.

GenExp: an interactive web-based genomic DAS client with client-side data rendering

Background

The Distributed Annotation System (DAS) offers a standard protocol for sharing and integrating annotations on biological sequences. There are more than 1000 DAS sources available and the number is steadily increasing. Clients are an essential part of the DAS system and integrate data from several independent sources in order to create a useful representation to the user. While web-based DAS clients exist, most of them do not have direct interaction capabilities such as dragging and zooming with the mouse.

Results

Here we present GenExp, a web based and fully interactive visual DAS client. GenExp is a genome oriented DAS client capable of creating informative representations of genomic data zooming out from base level to complete chromosomes. It proposes a novel approach to genomic data rendering and uses the latest HTML5 web technologies to create the data representation inside the client browser. Thanks to client-side rendering most position changes do not need a network request to the server and so responses to zooming and panning are almost immediate. In GenExp it is possible to explore the genome intuitively moving it with the mouse just like geographical map applications. Additionally, in GenExp it is possible to have more than one data viewer at the same time and to save the current state of the application to revisit it later on.

Conclusions

GenExp is a new interactive web-based client for DAS and addresses some of the short-comings of the existing clients. It uses client-side data rendering techniques resulting in easier genome browsing and exploration. GenExp is open source under the GPL license and it is freely available at http://gralggen.lsi.upc.edu/recerca/genexp.

Semantic-JSON: a lightweight web service interface for Semantic Web contents integrating multiple life science databases

Global cloud frameworks for bioinformatics research databases become huge and heterogeneous; solutions face various diametric challenges comprising cross-integration, retrieval, security and openness. To address this, as of March 2011 organizations including RIKEN published 192 mammalian, plant and protein life sciences databases having 8.2 million data records, integrated as Linked Open or Private Data (LOD/LPD) using SciNetS.org, the Scientists' Networking System. The huge quantity of linked data this database integration framework covers is based on the Semantic Web, where researchers collaborate by managing metadata across public and private databases in a secured data space. This outstripped the data query capacity of existing interface tools like SPARQL. Actual research also requires specialized tools for data analysis using raw original data. To solve these challenges, in December 2009 we developed the lightweight Semantic-JSON interface to access each fragment of linked and raw life sciences data securely under the control of programming languages popularly used by bioinformaticians such as Perl and Ruby. Researchers successfully used the interface across 28 million semantic relationships for biological applications including genome design, sequence processing, inference over phenotype databases, full-text search indexing and human-readable contents like ontology and LOD tree viewers. Semantic-JSON services of SciNetS.org are provided at http://semanticjson.org.

DAS writeback: a collaborative annotation system

BACKGROUND

Centralised resources such as GenBank and UniProt are perfect examples of the major international efforts that have been made to integrate and share biological information. However, additional data that adds value to these resources needs a simple and rapid route to public access. The Distributed Annotation System (DAS) provides an adequate environment to integrate genomic and proteomic information from multiple sources, making this information accessible to the community. DAS offers a way to distribute and access information but it does not provide domain experts with the mechanisms to participate in the curation process of the available biological entities and their annotations.

RESULTS

We designed and developed a Collaborative Annotation System for proteins called DAS Writeback. DAS writeback is a protocol extension of DAS to provide the functionalities of adding, editing and deleting annotations. We implemented this new specification as extensions of both a DAS server and a DAS client. The architecture was designed with the involvement of the DAS community and it was improved after performing usability experiments emulating a real annotation task.

CONCLUSIONS

We demonstrate that DAS Writeback is effective, usable and will provide the appropriate environment for the creation and evolution of community protein annotation.

An informatics project and online "Knowledge Centre" supporting modern genotype-to-phenotype research

Explosive growth in the generation of genotype-to-phenotype (G2P) data necessitates a concerted effort to tackle the logistical and informatics challenges this presents. The GEN2PHEN Project represents one such effort, with a broad strategy of uniting disparate G2P resources into a hybrid centralized-federated network. This is achieved through a holistic strategy focussed on three overlapping areas: data input standards and pipelines through which to submit and collect data (data in); federated, independent, extendable, yet interoperable database platforms on which to store and curate widely diverse datasets (data storage); and data formats and mechanisms with which to exchange, combine, and extract data (data exchange and output). To fully leverage this data network, we have constructed the "G2P Knowledge Centre" (http://www.gen2phen.org). This central platform provides holistic searching of the G2P data domain allied with facilities for data annotation and user feedback, access to extensive G2P and informatics resources, and tools for constructing online working communities centered on the G2P domain. Through the efforts of GEN2PHEN, and through combining data with broader community-derived knowledge, the Knowledge Centre opens up exciting possibilities for organizing, integrating, sharing, and interpreting new waves of G2P data in a collaborative fashion.

Dalliance: interactive genome viewing on the web

SUMMARY

Dalliance is a new genome viewer which offers a high level of interactivity while running within a web browser. All data is fetched using the established distributed annotation system (DAS) protocol, making it easy to customize the browser and add extra data.

AVAILABILITY AND IMPLEMENTATION

Dalliance runs entirely within your web browser, and relies on existing DAS server infrastructure. Browsers for several mammalian genomes are available at http://www.biodalliance.org/, and the use of DAS means you can add your own data to these browsers. In addition, the source code (Javascript) is available under the BSD license, and is straightforward to install on your own web server and embed within other documents.

easyDAS: automatic creation of DAS servers

Background

The Distributed Annotation System (DAS) has proven to be a successful way to publish and share biological data. Although there are more than 750 active registered servers from around 50 organizations, setting up a DAS server comprises a fair amount of work, making it difficult for many research groups to share their biological annotations. Given the clear advantage that the generalized sharing of relevant biological data is for the research community it would be desirable to facilitate the sharing process.

Results

Here we present easyDAS, a web-based system enabling anyone to publish biological annotations with just some clicks. The system, available at http://www.ebi.ac.uk/panda-srv/easydas is capable of reading different standard data file formats, process the data and create a new publicly available DAS source in a completely automated way. The created sources are hosted on the EBI systems and can take advantage of its high storage capacity and network connection, freeing the data provider from any network management work. easyDAS is an open source project under the GNU LGPL license.

Conclusions

easyDAS is an automated DAS source creation system which can help many researchers in sharing their biological data, potentially increasing the amount of relevant biological data available to the scientific community.

Analysing proteomics identifications in the context of functional and structural protein annotation: integrating annotation using PICR, DAS, and BioMart

For many species, there is a wealth of detailed annotation of individual proteins available to the proteomics researcher. Accessing and making the best use of this annotation can be problematic in the absence of suitable bioinformatics support. This chapter explores some of the technologies and tools that allow protein annotation to be accessed and collated from multiple sources. The intended audience is the proteomics scientist who has limited or no access to bioinformatics/programming support and wishes to make the best use of existing resources to annotate sets of protein identifications derived from mass spectrometry and related techniques.

Current trends and new challenges of databases and web applications for systems driven biological research

Dynamic and rapidly evolving nature of systems driven research imposes special requirements on the technology, approach, design and architecture of computational infrastructure including database and Web application. Several solutions have been proposed to meet the expectations and novel methods have been developed to address the persisting problems of data integration. It is important for researchers to understand different technologies and approaches. Having familiarized with the pros and cons of the existing technologies, researchers can exploit its capabilities to the maximum potential for integrating data. In this review we discuss the architecture, design and key technologies underlying some of the prominent databases and Web applications. We will mention their roles in integration of biological data and investigate some of the emerging design concepts and computational technologies that are likely to have a key role in the future of systems driven biomedical research.

Proteomics data repositories: providing a safe haven for your data and acting as a springboard for further research

Despite the fact that data deposition is not a generalised fact yet in the field of proteomics, several mass spectrometry (MS) based proteomics repositories are publicly available for the scientific community. The main existing resources are: the Global Proteome Machine Database (GPMDB), PeptideAtlas, the PRoteomics IDEntifications database (PRIDE), Tranche, and NCBI Peptidome. In this review the capabilities of each of these will be described, paying special attention to four key properties: data types stored, applicable data submission strategies, supported formats, and available data mining and visualization tools. Additionally, the data contents from model organisms will be enumerated for each resource. There are other valuable smaller and/or more specialized repositories but they will not be covered in this review. Finally, the concept behind the ProteomeXchange consortium, a collaborative effort among the main resources in the field, will be introduced.

AnnoTrack--a tracking system for genome annotation

Background

As genome sequences are determined for increasing numbers of model organisms, demand has grown for better tools to facilitate unified genome annotation efforts by communities of biologists. Typically this process involves numerous experts from the field and the use of data from dispersed sources as evidence. This kind of collaborative annotation project requires specialized software solutions for efficient data tracking and processing.

Results

As part of the scale-up phase of the ENCODE project (Encyclopedia of DNA Elements), the aim of the GENCODE project is to produce a highly accurate evidence-based reference gene annotation for the human genome. The AnnoTrack software system was developed to aid this effort. It integrates data from multiple distributed sources, highlights conflicts and facilitates the quick identification, prioritisation and resolution of problems during the process of genome annotation.

Conclusions

AnnoTrack has been in use for the last year and has proven a very valuable tool for large-scale genome annotation. Designed to interface with standard bioinformatics components, such as DAS servers and Ensembl databases, it is easy to setup and configure for different genome projects. The source code is available at http://annotrack.sanger.ac.uk.

Next generation tools for genomic data generation, distribution, and visualization

Background

With the rapidly falling cost and availability of high throughput sequencing and microarray technologies, the bottleneck for effectively using genomic analysis in the laboratory and clinic is shifting to one of effectively managing, analyzing, and sharing genomic data.

Results

Here we present three open-source, platform independent, software tools for generating, analyzing, distributing, and visualizing genomic data. These include a next generation sequencing/microarray LIMS and analysis project center (GNomEx); an application for annotating and programmatically distributing genomic data using the community vetted DAS/2 data exchange protocol (GenoPub); and a standalone Java Swing application (GWrap) that makes cutting edge command line analysis tools available to those who prefer graphical user interfaces. Both GNomEx and GenoPub use the rich client Flex/Flash web browser interface to interact with Java classes and a relational database on a remote server. Both employ a public-private user-group security model enabling controlled distribution of patient and unpublished data alongside public resources. As such, they function as genomic data repositories that can be accessed manually or programmatically through DAS/2-enabled client applications such as the Integrated Genome Browser.

Conclusions

These tools have gained wide use in our core facilities, research laboratories and clinics and are freely available for non-profit use. See http://sourceforge.net/projects/gnomex/, http://sourceforge.net/projects/genoviz/, and http://sourceforge.net/projects/useq.

Choosing a genome browser for a Model Organism Database: surveying the maize community

As the B73 maize genome sequencing project neared completion, MaizeGDB began to integrate a graphical genome browser with its existing web interface and database. To ensure that maize researchers would optimally benefit from the potential addition of a genome browser to the existing MaizeGDB resource, personnel at MaizeGDB surveyed researchers' needs. Collected data indicate that existing genome browsers for maize were inadequate and suggest implementation of a browser with quick interface and intuitive tools would meet most researchers' needs. Here, we document the survey's outcomes, review functionalities of available genome browser software platforms and offer our rationale for choosing the GBrowse software suite for MaizeGDB. Because the genome as represented within the MaizeGDB Genome Browser is tied to detailed phenotypic data, molecular marker information, available stocks, etc., the MaizeGDB Genome Browser represents a novel mechanism by which the researchers can leverage maize sequence information toward crop improvement directly. Database URL: http://gbrowse.maizegdb.org/

Using the ensembl genome server to browse genomic sequence data

The Ensembl project provides a comprehensive source of automatic annotation of the human genome sequence, as well as other species of biomedical interest, with confirmed gene predictions that have been integrated with external data sources. This unit describes how to use the Ensembl genome browser (http://www.ensembl.org/), the public interface of the project. It describes how to find a gene or protein of interest, how to get additional information and external links, and how to use the comparative genomic data. Curr. Protoc. Bioinform. 30:1.15.1-1.15.48. (c) 2010 by John Wiley & Sons, Inc.

BioGPS: an extensible and customizable portal for querying and organizing gene annotation resources

BioGPS is a community based customisable gene annotation portal bringing together gene annotation resources on to a single platform.

Online gene annotation resources are indispensable for analysis of genomics data. However, the landscape of these online resources is highly fragmented, and scientists often visit dozens of these sites for each gene in a candidate gene list. Here, we introduce BioGPS http://biogps.gnf.org, a centralized gene portal for aggregating distributed gene annotation resources. Moreover, BioGPS embraces the principle of community intelligence, enabling any user to easily and directly contribute to the BioGPS platform.

Ensembl Genomes: extending Ensembl across the taxonomic space

Ensembl Genomes (http://www.ensemblgenomes.org) is a new portal offering integrated access to genome-scale data from non-vertebrate species of scientific interest, developed using the Ensembl genome annotation and visualisation platform. Ensembl Genomes consists of five sub-portals (for bacteria, protists, fungi, plants and invertebrate metazoa) designed to complement the availability of vertebrate genomes in Ensembl. Many of the databases supporting the portal have been built in close collaboration with the scientific community, which we consider as essential for maintaining the accuracy and usefulness of the resource. A common set of user interfaces (which include a graphical genome browser, FTP, BLAST search, a query optimised data warehouse, programmatic access, and a Perl API) is provided for all domains. Data types incorporated include annotation of (protein and non-protein coding) genes, cross references to external resources, and high throughput experimental data (e.g. data from large scale studies of gene expression and polymorphism visualised in their genomic context). Additionally, extensive comparative analysis has been performed, both within defined clades and across the wider taxonomy, and sequence alignments and gene trees resulting from this can be accessed through the site.