Abstract: For a number of years the BioMart data warehousing system has proven to be a valuable resource for scientists seeking a fast and versatile means of accessing the growing volume of genomic data provided by the Ensembl project. The launch of the Ensembl Genomes project in 2009 complemented the Ensembl project by utilizing the same visualization, interactive and programming tools to provide users with a means for accessing genome data from a further five domains: protists, bacteria, metazoa, plants and fungi. The Ensembl and Ensembl Genomes BioMarts provide a point of access to the high-quality gene annotation, variation data, functional and regulatory annotation and evolutionary relationships from genomes spanning the taxonomic space. This article aims to give a comprehensive overview of the Ensembl and Ensembl Genomes BioMarts as well as some useful examples and a description of current data content and future objectives. Database URLs: http://www.ensembl.org/biomart/martview/; http://metazoa.ensembl.org/biomart/martview/; http://plants.ensembl.org/biomart/martview/; http://protists.ensembl.org/biomart/martview/; http://fungi.ensembl.org/biomart/martview/; http://bacteria.ensembl.org/biomart/martview/.

Abstract: The International Cancer Genome Consortium (ICGC) is a collaborative effort to characterize genomic abnormalities in 50 different cancer types. To make this data available, the ICGC has created the ICGC Data Portal. Powered by the BioMart software, the Data Portal allows each ICGC member institution to manage and maintain its own databases locally, while seamlessly presenting all the data in a single access point for users. The Data Portal currently contains data from 24 cancer projects, including ICGC, The Cancer Genome Atlas (TCGA), Johns Hopkins University, and the Tumor Sequencing Project. It consists of 3478 genomes and 13 cancer types and subtypes. Available open access data types include simple somatic mutations, copy number alterations, structural rearrangements, gene expression, microRNAs, DNA methylation and exon junctions. Additionally, simple germline variations are available as controlled access data. The Data Portal uses a web-based graphical user interface (GUI) to offer researchers multiple ways to quickly and easily search and analyze the available data. The web interface can assist in constructing complicated queries across multiple data sets. Several application programming interfaces are also available for programmatic access. Here we describe the organization, functionality, and capabilities of the ICGC Data Portal.

Abstract: The past decade has witnessed the modern advances of high-throughput technology and rapid growth of research capacity in producing large-scale biological data, both of which were concomitant with an exponential growth of biomedical literature. This wealth of scholarly knowledge is of significant importance for researchers in making scientific discoveries and healthcare professionals in managing health-related matters. However, the acquisition of such information is becoming increasingly difficult due to its large volume and rapid growth. In response, the National Center for Biotechnology Information (NCBI) is continuously making changes to its PubMed Web service for improvement. Meanwhile, different entities have devoted themselves to developing Web tools for helping users quickly and efficiently search and retrieve relevant publications. These practices, together with maturity in the field of text mining, have led to an increase in the number and quality of various Web tools that provide comparable literature search service to PubMed. In this study, we review 28 such tools, highlight their respective innovations, compare them to the PubMed system and one another, and discuss directions for future development. Furthermore, we have built a website dedicated to tracking existing systems and future advances in the field of biomedical literature search. Taken together, our work serves information seekers in choosing tools for their needs and service providers and developers in keeping current in the field. Database URL: http://www.ncbi.nlm.nih.gov/CBBresearch/Lu/search

Abstract: Biological data management is a challenging undertaking. It is challenging for database designers, because biological concepts are complex and not always well defined, and therefore the data models that are used to represent them are constantly changing as new techniques are developed and new information becomes available. It is challenging for collaborating groups based in different geographical locations who wish to have unified access to their distributed data sources, because combining and presenting their data creates logistical difficulties. Finally, it is challenging for users of biological databases, because in order to correctly interpret the experimental data located in one database, additional information from other databases is frequently needed, requiring the user to learn multiple systems. The BioMart project (www.biomart.org) was initiated to address these challenges. The BioMart software is based on two fundamental concepts: data agnostic modelling and data federation. Data agnostic modelling simplifies the difficult and time-consuming task of data modelling. In BioMart, this is achieved by using a predefined, query-optimized relational schema that can be used to represent any kind of data (1). Data federation makes it possible to organize multiple, disparate and distributed database systems into what appears to be a single integrated virtual database. It therefore allows users to access and cross reference data from these data sources using a single user interface, without the need for database administrators to physically collate the data in one location. Using these fundamental concepts, the BioMart project has driven a change in the biological data management paradigm, where individual biological databases are managed by different custom built systems. To give more control to both the users and the data providers, a new, innovative solution was required. BioMart started by adapting data warehousing ideas to create one universal software system for biological data management and empower biologists with the ability to create complex, customized datasets through a web interface without the need for bioinformatics support (1). It subsequently introduced a new innovative way of creating large multi-database repositories that avoid the need to store all the data in a single location (2), and finally it proved that large-scale projects involving next generation sequencing data can be managed efficiently in a distributed environment (3). BioMart has successfully adapted data warehousing ideas such as data marts, dimensional modelling (4), and query optimization into the world of biological databases (5–13). BioMart's ability to quickly deploy a website hosting any type of data, user-friendly graphical user interface, several programmatic interfaces and support for third party tools contributed to its success and adoption by many different types of projects around the world as their data management platform (14). During the 10 years of its existence, BioMart has grown from humble beginnings as a ‘data mining extension’ for the Ensembl website (1), to become an international collaboration involving large number of different organizations located on five continents: Asia, Australia, Europe, North America and South America (3,15). It has a large community of users and developers and it has been successfully used in both academia and industry. The latest version of the BioMart software has been significantly enhanced with numerous graphical user interfaces that are tailored to different user groups. In addition, it has been further improved by parallel query processing, it is now extensible with different analysis tools and the installation process can be effortlessly completed with just a few mouse clicks (16). Building on the wealth of information that has become accessible through the BioMart interface, the BioMart Central Portal (15) has introduced an innovative alternative to the large data stores maintained by specialized organizations such as The European Bioinformatics Institute (EBI) or The National Center for Biotechnology Information (NCBI). BioMart Central Portal is a first-of-its-kind, community-driven effort to provide unified access to dozens of biological databases. All development and maintenance of individual databases is left to the individual data providers, making it a very cost-effective approach. The groups that maintain individual sources can do so at their own location without the necessity of any data exchange procedures. In addition, they can draw on the wealth of information available through the portal to expose their data in the context of third party annotations. The BioMart Central Portal approach is very democratic: everyone can join or remove their data source at any time. BioMart Central Portal is effectively a ‘Virtual Bioinformatics Institute’ with no onsite personnel, minimal administration, and a very ‘green’ footprint. More recently, the International Cancer Genome Consortium (ICGC) Data Portal has demonstrated how BioMart can scale to manage large collaborative projects involving next generation sequencing data (3). The ICGC is generating data on an unprecedented scale by sequencing 500 cancer genomes and matched normal control genomes for 50 different cancer types (17). The effort is distributed between multiple participating countries and sequencing centres. Given the scale of the effort, moving all of the data to a single location is impractical. Instead, the ICGC Data Portal relies on BioMart data federation. By replicating and distributing the data model across different centres that produce the same type of data according to the same recipe, the scalability of the effort is greatly improved. Each centre is only responsible for managing their own data while data access to all of the consortium data is managed by the BioMart software. This presents a scalable approach, not only in the traditional sense of parallelizing data processing and storage, but also in a more general sense of outsourcing the external annotation expertise by federating annotations from additional, independently-maintained databases that are available in the BioMart Central Portal. The future developments for BioMart involve specialized ‘pre-packaged’ and reusable data portals. One example already in development is the OncoPortal, aimed at researchers managing cancer data. It will include preconfigured access to sources of annotations that are useful for cancer research such as Ensembl (5), Reactome (12), COSMIC (9), Pancreatic Expression Database (10) and others. It will also include a set of tools that are specifically designed for cancer data analysis. There are plans to build other preconfigured portals for different research areas, such as a mouse portal and a model organism portal. It is an ambition of the BioMart community that the BioMart project remains at the forefront of innovative solutions for biological data management in the years to come. By creating these specialized solutions and further reducing the barriers to entry, the aim is to encourage more groups to share their data through BioMart, thereby further enhancing the entire BioMart community.

Abstract: The Biomolecular Interaction Network Database (BIND) is a major source of curated biomolecular interactions, which has been unmaintained for the last few years, a trend which will eventually result in the loss of a significant amount of unique biomolecular interaction information, mostly as database identifiers become out of date. To help reverse this trend, we converted BIND to a standard format, Proteomics Standard Initiative-Molecular Interaction 2.5, starting from the last curated data release (from 2005) available in a custom XML format and made the core components (interactions and complexes) plus additional valuable curated information available for download (http://download.baderlab.org/BINDTranslation/). Major work during the conversion process was required to update out of date molecule identifiers resulting in a more comprehensive conversion of BIND, by measures including number of species and interactor types covered, than what is currently accessible elsewhere. This work also highlights issues of data modeling, controlled vocabulary adoption and data cleaning that can serve as a general case study on the future compatibility of interaction databases. Database URL: http://download.baderlab.org/BINDTranslation/

Abstract: BioMart is a freely available, open source, federated database system that provides a unified access to disparate, geographically distributed data sources. It is designed to be data agnostic and platform independent, such that existing databases can easily be incorporated into the BioMart framework. BioMart allows databases hosted on different servers to be presented seamlessly to users, facilitating collaborative projects between different research groups. BioMart contains several levels of query optimization to efficiently manage large data sets and offers a diverse selection of graphical user interfaces and application programming interfaces to ensure that queries can be performed in whatever manner is most convenient for the user. The software has now been adopted by a large number of different biological databases spanning a wide range of data types and providing a rich source of annotation available to bioinformaticians and biologists alike. Database URL: http://www.biomart.org

Abstract: Recent technological advances have lead to the ability to generate large amounts of data for model and non-model organisms. Whereas, in the past, there have been a relatively small number of central repositories that serve genomic data, an increasing number of distinct specialized data repositories and resources have been established. Here, we describe a generic approach that provides for the integration of a diverse spectrum of data resources into a unified analysis framework, Galaxy (http://usegalaxy.org). This approach allows the simplified coupling of external data resources with the data analysis tools available to Galaxy users, while leveraging the native data mining facilities of the external data resources. DATABASE URL: http://usegalaxy.org.

Abstract: Antibiotic resistance in bacteria is often due to acquisition of resistance genes associated with different mobile genetic elements. In Gram-negative bacteria, many resistance genes are found as part of small mobile genetic elements called gene cassettes, generally found integrated into larger elements called integrons. Integrons carrying antibiotic resistance gene cassettes are often associated with mobile elements and here are designated 'mobile resistance integrons' (MRIs). More than one cassette can be inserted in the same integron to create arrays that contribute to the spread of multi-resistance. In many sequences in databases such as GenBank, only the genes within cassettes, rather than whole cassettes, are annotated and the same gene/cassette may be given different names in different entries, hampering analysis. We have developed the Repository of Antibiotic resistance Cassettes (RAC) website to provide an archive of gene cassettes that includes alternative gene names from multiple nomenclature systems and allows the community to contribute new cassettes. RAC also offers an additional function that allows users to submit sequences containing cassettes or arrays for annotation using the automatic annotation system Attacca. Attacca recognizes features (gene cassettes, integron regions) and identifies cassette arrays as patterns of features and can also distinguish minor cassette variants that may encode different resistance phenotypes (aacA4 cassettes and bla cassettes-encoding β-lactamases). Gaps in annotations are manually reviewed and those found to correspond to novel cassettes are assigned unique names. While there are other websites dedicated to integrons or antibiotic resistance genes, none includes a complete list of antibiotic resistance gene cassettes in MRI or offers consistent annotation and appropriate naming of all of these cassettes in submitted sequences. RAC thus provides a unique resource for researchers, which should reduce confusion and improve the quality of annotations of gene cassettes in integrons associated with antibiotic resistance. DATABASE URL: http://www2.chi.unsw.edu.au/rac.

Abstract: Eukaryotic chromatin is composed of DNA and protein components—core histones—that act to compactly pack the DNA into nucleosomes, the fundamental building blocks of chromatin. These nucleosomes are connected to adjacent nucleosomes by linker histones. Nucleosomes are highly dynamic and, through various core histone post-translational modifications and incorporation of diverse histone variants, can serve as epigenetic marks to control processes such as gene expression and recombination. The Histone Sequence Database is a curated collection of sequences and structures of histones and non-histone proteins containing histone folds, assembled from major public databases. Here, we report a substantial increase in the number of sequences and taxonomic coverage for histone and histone fold-containing proteins available in the database. Additionally, the database now contains an expanded dataset that includes archaeal histone sequences. The database also provides comprehensive multiple sequence alignments for each of the four core histones (H2A, H2B, H3 and H4), the linker histones (H1/H5) and the archaeal histones. The database also includes current information on solved histone fold-containing structures. The Histone Sequence Database is an inclusive resource for the analysis of chromatin structure and function focused on histones and histone fold-containing proteins. Database URL: The Histone Sequence Database is freely available and can be accessed at http://research.nhgri.nih.gov/histones/.

Abstract: The vast majority of genes in humans and other organisms undergo alternative splicing, yet the biological function of splice variants is still very poorly understood in large part because of the lack of simple tools that can map the expression profiles and patterns of these variants with high sensitivity. High-throughput quantitative real-time polymerase chain reaction (qPCR) is an ideal technique to accurately quantify nucleic acid sequences including splice variants. However, currently available primer design programs do not distinguish between splice variants and also differ substantially in overall quality, functionality or throughput mode. Here, we present GETPrime, a primer database supported by a novel platform that uniquely combines and automates several features critical for optimal qPCR primer design. These include the consideration of all gene splice variants to enable either gene-specific (covering the majority of splice variants) or transcript-specific (covering one splice variant) expression profiling, primer specificity validation, automated best primer pair selection according to strict criteria and graphical visualization of the latter primer pairs within their genomic context. GETPrime primers have been extensively validated experimentally, demonstrating high transcript specificity in complex samples. Thus, the free-access, user-friendly GETPrime database allows fast primer retrieval and visualization for genes or groups of genes of most common model organisms, and is available at http://updepla1srv1.epfl.ch/getprime/. Database URL: http://deplanckelab.epfl.ch.

Abstract: Protein ubiquitination is an evolutionarily conserved and functionally diverse post-translational modification achieved through the sequential action of E1-activating enzymes, E2-conjugating enzymes and E3 ligases A summary of validated ubiquitination substrates have been presented and a prediction of new substrates have been conducted in yeast However, a systematic summary of human ubiquitination substrates containing experimental evidence and the enzymatic cascade of each substrate is not available In the present study, hUbiquitome web resource is introduced, a public resource for the retrieval of experimentally verified human ubiquitination enzymes and substrates hUbiquitome is the first comprehensive database of human ubiquitination cascades Currently, hUbiquitome has in its repertoire curated data comprising 1 E1 enzyme, 12 E2 enzymes, 138 E3 ligases or complexes, 279 different substrate proteins and 17 deubiquitination enzyme terms The biological functions of substrates from different kinds of E3s were analyzed using the collected data The findings show that substrates ubiquitinated by RING (Really Interesting New Gene) E3s are enriched most in apoptosis-related processes, whereas substrates ubiquitinated by other E3s are enriched in gene expression-associated processes An analysis of the data demonstrates the biological process preferences of the different kinds of E3s hUbiquitome is the first database to systematically collect experimentally validated ubiquitinated proteins and related ubiquitination cascade enzymes which might be helpful in the field of ubiquitination-modification research Database URL: http://20238126151/hmdd/hubi/

Abstract: Parkinson's disease (PD) is a common, adult-onset, neuro-degenerative disorder characterized by the degeneration of cardinal motor signs mainly due to the loss of dopaminergic neurons in the substantia nigra. To date, researchers still have limited understanding of the key molecular events that provoke neurodegeneration in this disease. Here, we present ParkDB, the first queryable database dedicated to gene expression in PD. ParkDB contains a complete set of re-analyzed, curated and annotated microarray datasets. This resource enables scientists to identify and compare expression signatures involved in PD and dopaminergic neuron differentiation under different biological conditions and across species. Database URL: http://www2.cancer.ucl.ac.uk/Parkinson_Db2/

Abstract: The National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) Central Repository makes data and biospecimens from NIDDK-funded research available to the broader scientific community. It thereby facilitates: the testing of new hypotheses without new data or biospecimen collection; pooling data across several studies to increase statistical power; and informative genetic analyses using the Repository's well-curated phenotypic data. This article describes the initial database plan for the Repository and its revision using a simpler model. Among the lessons learned were the trade-offs between the complexity of a database design and the costs in time and money of implementation; the importance of integrating consent documents into the basic design; the crucial need for linkage files that associate biospecimen IDs with the masked subject IDs used in deposited data sets; and the importance of standardized procedures to test the integrity data sets prior to distribution. The Repository is currently tracking 111 ongoing NIDDK-funded studies many of which include genotype data, and it houses over 5 million biospecimens of more than 25 types including serum, plasma, stool, urine, DNA, red blood cells, buffy coat and tissue. Repository resources have supported a range of biochemical, clinical, statistical and genetic research (188 external requests for clinical data and 31 for biospecimens have been approved or are pending). Genetic research has included GWAS, validation studies, development of methods to improve statistical power of GWAS and testing of new statistical methods for genetic research. We anticipate that the future impact of the Repository's resources on biomedical research will be enhanced by (i) cross-listing of Repository biospecimens in additional searchable databases and biobank catalogs; (ii) ongoing deployment of new applications for querying the contents of the Repository; and (iii) increased harmonization of procedures, data collection strategies, questionnaires etc. across both research studies and within the vocabularies used by different repositories.

Abstract: A database of thermodynamic properties is developed, which extends a previous database of glycolysis and tricarboxylic acid cycle by adding the reactions of the pentose phosphate pathway. The raw data and documented estimations of solution properties are made electronically available. The database is determined by estimation of a set of parameters representing species-level free energies of formation. The resulting calculations provide thermodynamic and network-based estimates of thermodynamic properties for six reactions of the pentose phosphate pathway for which estimates are not available in the preexisting literature. Optimized results are made available in ThermoML format. Because calculations depend on estimated hydrogen and metal cation dissociation constants, an uncertainty and sensitivity analysis is performed, revealing 23 critical dissociation constants to which the computed thermodynamic properties are particularly sensitive. DATABASE URL: http://www.biocoda.org/thermo

Abstract: We previously developed NetPath as a resource for comprehensive manually curated signal transduction pathways. The pathways in NetPath contain a large number of molecules and reactions which can sometimes be difficult to visualize or interpret given their complexity. To overcome this potential limitation, we have developed a set of more stringent curation and inclusion criteria for pathway reactions to generate high-confidence signaling maps. NetSlim is a new resource that contains this ‘core’ subset of reactions for each pathway for easy visualization and manipulation. The pathways in NetSlim are freely available at http://www.netpath.org/netslim. Database URL: www.netpath.org/netslim

Abstract: Linking phenotypic with genotypic diversity has become a major requirement for basic and applied genome-centric biological research. To meet this need, a comprehensive database backend for efficiently storing, querying and analyzing large experimental data sets is necessary. Chado, a generic, modular, community-based database schema is widely used in the biological community to store information associated with genome sequence data. To meet the need to also accommodate large-scale phenotyping and genotyping projects, a new Chado module called Natural Diversity has been developed. The module strictly adheres to the Chado remit of being generic and ontology driven. The flexibility of the new module is demonstrated in its capacity to store any type of experiment that either uses or generates specimens or stock organisms. Experiments may be grouped or structured hierarchically, whereas any kind of biological entity can be stored as the observed unit, from a specimen to be used in genotyping or phenotyping experiments, to a group of species collected in the field that will undergo further lab analysis. We describe details of the Natural Diversity module, including the design approach, the relational schema and use cases implemented in several databases.

Abstract: Many abbreviations are used in the literature especially in the life sciences, and polysemous abbreviations appear frequently, making it difficult to read and understand scientific papers that are outside of a reader's expertise. Thus, we have developed Allie, a database and a search service of abbreviations and their long forms (a.k.a. full forms or definitions). Allie searches for abbreviations and their corresponding long forms in a database that we have generated based on all titles and abstracts in MEDLINE. When a user query matches an abbreviation, Allie returns all potential long forms of the query along with their bibliographic data (i.e. title and publication year). In addition, for each candidate, co-occurring abbreviations and a research field in which it frequently appears in the MEDLINE data are displayed. This function helps users learn about the context in which an abbreviation appears. To deal with synonymous long forms, we use a dictionary called GENA that contains domain-specific terms such as gene, protein or disease names along with their synonymic information. Conceptually identical domain-specific terms are regarded as one term, and then conceptually identical abbreviation-long form pairs are grouped taking into account their appearance in MEDLINE. To keep up with new abbreviations that are continuously introduced, Allie has an automatic update system. In addition, the database of abbreviations and their long forms with their corresponding PubMed IDs is constructed and updated weekly. Database URL: The Allie service is available at http://allie.dbcls.jp/.

Abstract: The QlicRice database is designed to host publicly accessible, abiotic stress responsive quantitative trait loci (QTLs) in rice (Oryza sativa) and their corresponding sequenced gene loci It provides a platform for the data mining of abiotic stress responsive QTLs, as well as browsing and annotating associated traits, their location on a sequenced genome, mapped expressed sequence tags (ESTs) and tissue and growth stage-specific expressions on the whole genome Information on QTLs related to abiotic stresses and their corresponding loci from a genomic perspective has not yet been integrated on an accessible, user-friendly platform QlicRice offers client-responsive architecture to retrieve meaningful biological information—integrated and named ‘Qlic Search’—embedded in a query phrase autocomplete feature, coupled with multiple search options that include trait names, genes and QTL IDs A comprehensive physical and genetic map and vital statistics have been provided in a graphical manner for deciphering the position of QTLs on different chromosomes A convenient and intuitive user interface have been designed to help users retrieve associations to agronomically important QTLs on abiotic stress response in rice Database URL: http://nabgiasriresin:8080/qlic-rice/

Abstract: The model organism Encyclopedia of DNA Elements (modENCODE) project is a National Human Genome Research Institute (NHGRI) initiative designed to characterize the genomes of Drosophila melanogaster and Caenorhabditis elegans. A Data Coordination Center (DCC) was created to collect, store and catalog modENCODE data. An effective DCC must gather, organize and provide all primary, interpreted and analyzed data, and ensure the community is supplied with the knowledge of the experimental conditions, protocols and verification checks used to generate each primary data set. We present here the design principles of the modENCODE DCC, and describe the ramifications of collecting thorough and deep metadata for describing experiments, including the use of a wiki for capturing protocol and reagent information, and the BIR-TAB specification for linking biological samples to experimental results. modENCODE data can be found at http://www.modencode.org. Database URL: http://www.modencode.org.

Abstract: The Comprehensive Phytopathogen Genomics Resource (CPGR) provides a web-based portal for plant pathologists and diagnosticians to view the genome and trancriptome sequence status of 806 bacterial, fungal, oomycete, nematode, viral and viroid plant pathogens. Tools are available to search and analyze annotated genome sequences of 74 bacterial, fungal and oomycete pathogens. Oomycete and fungal genomes are obtained directly from GenBank, whereas bacterial genome sequences are downloaded from the A Systematic Annotation Package (ASAP) database that provides curation of genomes using comparative approaches. Curated lists of bacterial genes relevant to pathogenicity and avirulence are also provided. The Plant Pathogen Transcript Assemblies Database provides annotated assemblies of the transcribed regions of 82 eukaryotic genomes from publicly available single pass Expressed Sequence Tags. Data-mining tools are provided along with tools to create candidate diagnostic markers, an emerging use for genomic sequence data in plant pathology. The Plant Pathogen Ribosomal DNA (rDNA) database is a resource for pathogens that lack genome or transcriptome data sets and contains 131 755 rDNA sequences from GenBank for 17 613 species identified as plant pathogens and related genera.

Abstract: Compositional bias (i.e. a skew in the composition of a biological sequence towards a subset of residue types) can occur at a wide variety of scales, from compositional biases of whole genomes, down to short regions in individual protein and gene-DNA sequences that are compositionally biased (CB regions). Such CB regions are made from a subset of residue types that are strewn along the length of the region in an irregular way. Here, we have developed the database server LPS-annotate, for the analysis of such CB regions, and protein disorder in protein sequences. The algorithm defines compositional bias through a thorough search for lowest-probability subsequences (LPSs) (i.e., the least likely sequence regions in terms of composition). Users can (i) initially annotate CB regions in input protein or nucleotide sequences of interest, and then (ii) query a database of greater than 1,500,000 pre-calculated protein-CB regions, for investigation of further functional hypotheses and inferences, about the specific CB regions that were discovered, and their protein disorder propensities. We demonstrate how a user can search for CB regions of similar compositional bias and protein disorder, with a worked example. We show that our annotations substantially augment the CB-region annotations that already exist in the UniProt database, with more comprehensive annotation of more complex CB regions. Our analysis indicates tens of thousands of CB regions that do not comprise globular domains or transmembrane domains, and that do not have a propensity to protein disorder, indicating a large cohort of protein-CB regions of biophysically uncharacterized types. This server and database is a conceptually novel addition to the workbench of tools now available to molecular biologists to generate hypotheses and inferences about the proteins that they are investigating. It can be accessed at http://libaio.biol.mcgill.ca/lps-annotate.html. Database URL: http://libaio.biol.mcgill.ca/lps-annotate.html.

Abstract: In recent years, genomes from an increasing number of organisms have been sequenced, but their annotation remains a time-consuming process. The BioCyc databases offer a framework for the integrated analysis of metabolic networks. The Pathway tool software suite allows the automated construction of a database starting from an annotated genome, but it requires prior integration of all annotations into a specific summary file or into a GenBank file. To allow the easy creation and update of a BioCyc database starting from the multiple genome annotation resources available over time, we have developed an ad hoc data management system that we called Cyc Annotation Database System (CycADS). CycADS is centred on a specific database model and on a set of Java programs to import, filter and export relevant information. Data from GenBank and other annotation sources (including for example: KAAS, PRIAM, Blast2GO and PhylomeDB) are collected into a database to be subsequently filtered and extracted to generate a complete annotation file. This file is then used to build an enriched BioCyc database using the PathoLogic program of Pathway Tools. The CycADS pipeline for annotation management was used to build the AcypiCyc database for the pea aphid (Acyrthosiphon pisum) whose genome was recently sequenced. The AcypiCyc database webpage includes also, for comparative analyses, two other metabolic reconstruction BioCyc databases generated using CycADS: TricaCyc for Tribolium castaneum and DromeCyc for Drosophila melanogaster. Linked to its flexible design, CycADS offers a powerful software tool for the generation and regular updating of enriched BioCyc databases. The CycADS system is particularly suited for metabolic gene annotation and network reconstruction in newly sequenced genomes. Because of the uniform annotation used for metabolic network reconstruction, CycADS is particularly useful for comparative analysis of the metabolism of different organisms. Database URL: http://www.cycadsys.org.

Abstract: Web sites associated with the Eukaryotic Pathogen Bioinformatics Resource Center (EuPathDB.org) have recently introduced a graphical user interface, the Strategies WDK, intended to make advanced searching and set and interval operations easy and accessible to all users. With a design guided by usability studies, the system helps motivate researchers to perform dynamic computational experiments and explore relationships across data sets. For example, PlasmoDB users seeking novel therapeutic targets may wish to locate putative enzymes that distinguish pathogens from their hosts, and that are expressed during appropriate developmental stages. When a researcher runs one of the approximately 100 searches available on the site, the search is presented as a first step in a strategy. The strategy is extended by running additional searches, which are combined with set operators (union, intersect or minus), or genomic interval operators (overlap, contains). A graphical display uses Venn diagrams to make the strategy’s flow obvious. The interface facilitates interactive adjustment of the component searches with changes propagating forward through the strategy. Users may save their strategies, creating protocols that can be shared with colleagues. The strategy system has now been deployed on all EuPathDB databases, and successfully deployed by other projects. The Strategies WDK uses a configurable MVC architecture that is compatible with most genomics and biological warehouse databases, and is available for download at code.google.com/p/strategies-wdk. Database URL: www.eupathdb.org

Abstract: Video tutorials are an effective way for researchers to quickly learn how to use online tools offered by biological databases. At MaizeGDB, we have developed a number of video tutorials that demonstrate how to use various tools and explicitly outline the caveats researchers should know to interpret the information available to them. One such popular video currently available is ‘Using the MaizeGDB Genome Browser’, which describes how the maize genome was sequenced and assembled as well as how the sequence can be visualized and interacted with via the MaizeGDB Genome Browser. Database URL: http://www.maizegdb.org/

Abstract: The Caenorhabditis elegans genome sequence was published over a decade ago; this was the first published genome of a multi-cellular organism and now the WormBase project has had a decade of experience in curating this genome’s sequence and gene structures. In one of its roles as a central repository for nematode biology, WormBase continues to refine the gene structure annotations using sequence similarity and other computational methods, as well as information from the literature- and community-submitted annotations. We describe the various methods of gene structure curation that have been tried by WormBase and the problems associated with each of them. We also describe the current strategy for gene structure curation, and introduce the WormBase ‘curation tool’, which integrates different data sources in order to identify new and correct gene structures.

Abstract: The CEREALAB database aims to store genotypic and phenotypic data obtained by the CEREALAB project and to integrate them with already existing data sources in order to create a tool for plant breeders and geneticists. The database can help them in unravelling the genetics of economically important phenotypic traits; in identifying and choosing molecular markers associated to key traits; and in choosing the desired parentals for breeding programs. The database is divided into three sub-schemas corresponding to the species of interest: wheat, barley and rice; each sub-schema is then divided into two sub-ontologies, regarding genotypic and phenotypic data, respectively. Database URL: http://www.cerealab.unimore.it/jws/cerealab.jnlp

Abstract: Drug-induced QT interval prolongation is one of the most common reasons for the withdrawal of drugs from the market. In the past decade, at least nine drugs, i.e. terfenadine, astemizole, grepafloxacin, terodiline, droperidol, lidoflazine, sertindole, levomethadyl and cisapride, have been removed from the market or their use has been severely restricted because of drug-induced QT interval prolongation. Therefore, this irregularity is a major safety concern in the case of drugs submitted for regulatory approval. The most common mechanism of drug-induced QT interval prolongation may be drug-related inhibition of the human ether-a-go-go-related gene (hERG) channel, which subsequently results in prolongation of the cardiac action potential duration (APD). hERGAPDbase is a database of electrophysiological experimental data documenting potential hERG channel inhibitory actions and the APD-prolongation activities of chemical compounds. All data entries are manually collected from scientific papers and curated by a person. With hERGAPDbase, we aim to provide useful information for chemical and pharmacological scientists and enable easy access to electrophysiological experimental data on chemical compounds. Database URL: http://www.grt.kyushu-u.ac.jp/hergapdbase/

Abstract: Annotation using Gene Ontology (GO) terms is one of the most important ways in which biological information about specific gene products can be expressed in a searchable, computable form that may be compared across genomes and organisms. Because literature-based GO annotations are often used to propagate functional predictions between related proteins, their accuracy is critically important. We present a strategy that employs a comparison of literature-based annotations with computational predictions to identify and prioritize genes whose annotations need review. Using this method, we show that comparison of manually assigned ‘unknown’ annotations in the Saccharomyces Genome Database (SGD) with InterPro-based predictions can identify annotations that need to be updated. A survey of literature-based annotations and computational predictions made by the Gene Ontology Annotation (GOA) project at the European Bioinformatics Institute (EBI) across several other databases shows that this comparison strategy could be used to maintain and improve the quality of GO annotations for other organisms besides yeast. The survey also shows that although GOA-assigned predictions are the most comprehensive source of functional information for many genomes, a large proportion of genes in a variety of different organisms entirely lack these predictions but do have manual annotations. This underscores the critical need for manually performed, literature-based curation to provide functional information about genes that are outside the scope of widely used computational methods. Thus, the combination of manual and computational methods is essential to provide the most accurate and complete functional annotation of a genome.

Abstract: The Rat Genome Database (RGD) is the premier repository of rat genomic and genetic data and currently houses over 40 000 rat gene records as well as human and mouse orthologs, 1771 rat and 1911 human quantitative trait loci (QTLs) and 2209 rat strains. Biological information curated for these data objects includes disease associations, phenotypes, pathways, molecular functions, biological processes and cellular components. A suite of tools has been developed to aid curators in acquiring and validating data objects, assigning nomenclature, attaching biological information to objects and making connections among data types. The software used to assign nomenclature, to create and edit objects and to make annotations to the data objects has been specifically designed to make the curation process as fast and efficient as possible. The user interfaces have been adapted to the work routines of the curators, creating a suite of tools that is intuitive and powerful. Database URL: http://rgd.mcw.edu