http://precedings.nature.com/tags/database Recently posted documents tagged with 'database' Nature Publishing Group en Nature Precedings http://precedings.nature.com/images/header_logo.gif http://precedings.nature.com http://dx.doi.org/10.1038/npre.2009.3569.1 We are developing software applications to perform meta-analysis of microarray experiments based on standardized experiment annotations aiming to identify similar experiments and cluster experiments. The applications were tested on files obtained from the ArrayExpress public repository. Annotation terms were used to compute experiment dissimilarities to find experiments related to a query experiment. These applications may motivate efforts of bench biologists to better annotate experiments. http://dx.doi.org/10.1038/npre.2009.3569.1 Thu, 06 Aug 2009 20:01:12 UTC Annotation-based meta-analysis of microarray experiments doi:10.1038/npre.2009.3569.1 2009-08-06 Jie Zheng Nature Precedings 2009-08-06T20:01:12Z Poster Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2009.3471.1 Formal ontologies have made significant impact in bioscience over the last ten years. Among them, the Foundational Model of Anatomy Ontology (FMA) is the most comprehensive model for the spatio-structural representation of human anatomy. In the research project MEDICO we use the FMA as our main source of background knowledge about human anatomy. Our ultimate goals are to use spatial knowledge from the FMA (1) to improve automatic parsing algorithms for 3D volume data sets generated by Computed Tomography and Magnetic Resonance Imaging and (2) to generate semantic annotations using the concepts from the FMA to allow semantic search on medical image repositories. We argue that in this context more spatial relation instances are needed than those currently available in the FMA. In this publication we present a technique for the automatic inductive acquisition of spatial relation instances by generalizing from expert-annotated volume datasets. http://dx.doi.org/10.1038/npre.2009.3471.1 Mon, 27 Jul 2009 19:47:30 UTC Extending the Foundational Model of Anatomy with Automatically Acquired Spatial Relations doi:10.1038/npre.2009.3471.1 2009-07-27 Manuel Möller Nature Precedings 2009-07-27T19:47:30Z Manuscript Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2009.3467.1 One of the achievements of the eyeGENE Network is a repository of DNA samples of patients with inherited eye diseases and an associated database that tracks key elements of phenotype and genotype information for each patient. Although its database structure serves its direct research needs, eyeGENE has set a goal of enhancing this structure to become increasingly well integrated with medical information standards over time. This goal should be achieved by ensuring semantic interoperability with other information systems but without adopting the incoherencies and inconsistencies found in available biomedical standards. Therefore, eyeGENE’s current pragmatic perspective with focus on data and information, rather than what the information is about, should shift to a realism-based perspective that includes also the portion of reality described, and the competing opinions that clinicians may hold about it. An analysis of eyeGENE’s database structure and user interfaces suggests that such a transition is possible indeed. http://dx.doi.org/10.1038/npre.2009.3467.1 Mon, 27 Jul 2009 19:42:57 UTC Providing a Realist Perspective on the eyeGENE Database System doi:10.1038/npre.2009.3467.1 2009-07-27 Werner Ceusters Nature Precedings 2009-07-27T19:42:57Z Manuscript Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2009.3297.1 The GenitoUrinary Development Molecular Anatomy Project (GUDMAP) is a consortium of laboratories working to provide the scientific and medical community with gene expression data and tools to facilitate research (see www.gudmap.org). The data provided by GUDMAP includes large in situ hybridization screens (wholemount and section) and expression microarray analysis of components of the developing mouse urogenital system (including laser-captured material and FACS-isolated cells from transgenic reporter mice). In addition, a high-resolution anatomy ontology has been developed by members of the GUDMAP consortium to describe the subcompartments of the developing murine genitourinary tract. The GUDMAP Database Development Team and Editorial Office – both based in Edinburgh – function to ensure submission, curation, storage and presentation of the data submitted by the GUDMAP consortium. Our collective aim is twofold: 1) to simplify the process of submission so that data is publically available as soon as it is produced; and 2) to organize this information in a database and ensure that the online interface is continuously available and easy to use. Thus far, we have developed a range of tools that help both the submitter and the end user. These include: an online annotation tool that simplifies in situ data submission through an ontology-based graphical user interface; a database interface that allows users to browse and query expression data, and to filter data by organ system; a heat-map display of microarray data and analyses. Furthermore, the Edinburgh team has developed a GUDMAP Disease Database that queries associations between genes, genitourinary diseases, and renal/urinary and reproductive phenotypes. In collaboration with GUDMAP consortium members at the CCHMC (Cincinnati Children’s Hospital Medical Center), the Disease Database is being extended to include mammalian phenotypes mapped to OMIM entries. By virtue of its impressive dataset and its ease of use we hope that the GUDMAP Website will continue to serve as a powerful resource for biologists, clinicians and bioinformaticians with an interest in the urogenital system. http://dx.doi.org/10.1038/npre.2009.3297.1 Sat, 30 May 2009 14:17:58 UTC GUDMAP – An Online GenitoUrinary Resource doi:10.1038/npre.2009.3297.1 2009-05-30 Simon Harding Nature Precedings 2009-05-30T14:17:58Z Poster Developmental Biology Genetics & Genomics Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2009.3246.1 The Mouse Genome Informatics (MGI; http://www.informatics.jax.org) group is comprised of several collaborating projects including the Mouse Genome Database (MGD) Project, the Gene Expression Database (GXD) Project, the Mouse Tumor Biology (MTB) Database Project, and the Gene Ontology (GO) Project. Literature identification and collection is performed cooperatively amongst the groups.In recent years many institutional libraries have transitioned from a focus largely on print holdings to one of electronic access to journals. This change has necessitated adaptation on the part of the MGI curatorial group. Whereas the majority of journals covered by the group used to be surveyed in paper form, those journals are now surveyed electronically. Approximately 160 journals have been identified as those most relevant to the various database groups. Each curator in the group has the responsibility of scanning several journals for articles relevant to any of the database projects. Articles chosen via this process are marked as to their potential significance for various projects. Each article is catalogued in a Master Bibliography section of the MGI database system and annotated to the database sections for which it has been identified as relevant. A secondary triage process allows curators from each group to scan the chosen articles and mark ones desired for their project if such annotation has been missed on the initial scan.Once articles have been identified for each database project a variety of processes are implemented to further categorize and index data from those articles. For example, the Alleles and Phenotype section of the MGD database indexes each article marked for MGD and in this indexing process they identify each mouse gene and allele examined in the article. The GXD database indexing process has a different focus. In this case articles are indexed with regard to the stage of development used in the study as well as the assay technique used. In each case the indexing gives an overview of the data held in the article and assists in the more extensive curation performed in the following step of the curation process. Indexing also provides each group with valuable information used to prioritize and streamline the overall curation process.The MGI projects are supported by NHGRI grants HG000330, HG00273, and HG003622, NICHD grant HD033745, and NCI grant CA089713. http://dx.doi.org/10.1038/npre.2009.3246.1 Thu, 14 May 2009 21:29:18 UTC Literature Triage and Indexing in the Mouse Genome Informatics (MGI) Group doi:10.1038/npre.2009.3246.1 2009-05-14 Debra M. Krupke Nature Precedings 2009-05-14T21:29:18Z Poster Cancer Developmental Biology Genetics & Genomics Immunology Molecular Cell Biology Neuroscience Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2009.3245.1 Many advances in the field of cancer biology have been made using mouse models of human cancer. The Mouse Tumor Biology (MTB, http://tumor.informatics.jax.org) database provides web-based access to data on spontaneous and induced tumors from genetically defined mice (inbred, hybrid, mutant, and genetically engineered strains of mice). These data include standardized tumor names and classifications, pathology reports and images, mouse genetics, genomic and cytogenetic changes occurring in the tumor, strain names, tumor frequency and latency, and literature citations.Although primary source for the data represented in MTB is peer-reviewed scientific literature an increasing amount of data is derived from disparate sources. MTB includes annotated histopathology images and cytogenetic assay images for mouse tumors where these data are available from The Jackson Laboratory’s mouse colonies and from outside contributors. MTB encourages direct submission of mouse tumor data and images from the cancer research community and provides investigators with a web-accessible tool for image submission and annotation. Integrated searches of the data in MTB are facilitated by the use of several controlled vocabularies and by adherence to standard nomenclature. MTB also provides links to other related online resources such as the Mouse Genome Database, Mouse Phenome Database, the Biology of the Mammary Gland Web Site, Festing’s Listing of Inbred Strains of Mice, the JAX® Mice Web Site, and the Mouse Models of Human Cancers Consortium’s Mouse Repository. MTB provides access to data on mouse models of cancer via the internet and has been designed to facilitate the selection of experimental models for cancer research, the evaluation of mouse genetic models of human cancer, the review of patterns of mutations in specific cancers, and the identification of genes that are commonly mutated across a spectrum of cancers.MTB is supported by NCI grant CA089713. http://dx.doi.org/10.1038/npre.2009.3245.1 Wed, 13 May 2009 17:28:31 UTC Cancer Biology Data Curation at the Mouse Tumor Biology Database (MTB) doi:10.1038/npre.2009.3245.1 2009-05-13 Debra M. Krupke Nature Precedings 2009-05-13T17:28:31Z Poster Cancer Genetics & Genomics Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2009.3230.1 The International Union of Basic and Clinical Pharmacology database (IUPHAR-DB) integrates peer-reviewed pharmacological, chemical, genetic, functional and anatomical information on the 354 non-sensory G protein-coupled receptors (GPCRs), 71 ligand-gated ion channel subunits and 141 voltage-gated ion channel subunits encoded by the human, rat and mouse genomes. These genes represent the targets of about a third of currently approved drugs and are a major focus of drug discovery and development programs in the pharmaceutical industry. Individual gene pages provide a comprehensive description of the genes and their functions, with information on protein structure, ligands, expression patterns, signaling mechanisms, functional assays and biologically important receptor variants (e.g. single nucleotide polymorphisms and splice variants). The phenotypes resulting from altered gene expression (e.g. in genetically altered animals) and genetic mutations are described. Links are provided to bioinformatics resources such as NCBI RefSeq, OMIM, PubChem, human, rat and mouse genome databases. Recent developments include the addition of ligand-centered pages summarising information about unique ligand molecules in IUPHAR-DB. IUPHAR-DB represents a novel approach to biocuration because most data are provided through manual curation of published literature by a network of over 60 expert subcommittees coordinated by NC-IUPHAR. Data are referenced to the primary literature and linked to PubMed. The data are checked to ensure accuracy and consistency by the curators, added to the production server using custom-built submission tools and peer-reviewed by NC-IUPHAR, before being transferred to the public database. Data are reviewed and updated regularly (at least biennially). Other website features include comprehensive database search tools, online and downloadable gene lists and links to recent publications of interest to the field, such as reports on receptor-ligand pairings. The database is freely available at http://www.iuphar-db.org. Curators can be reached at curators [at] iuphar-db.org. We thank British Pharmacological Society, UNESCO (through the ICSU Grants Programme), Incyte, GlaxoSmithKline, Novartis, Servier and Wyeth for their support. http://dx.doi.org/10.1038/npre.2009.3230.1 Thu, 07 May 2009 18:58:20 UTC IUPHAR-DB: An Expert-Curated, Peer-Reviewed Database of Receptors and Ion Channels doi:10.1038/npre.2009.3230.1 2009-05-07 Joanna L. Sharman Nature Precedings 2009-05-07T18:58:20Z Poster Pharmacology Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2009.3218.1 GabiPD (http://www.gabipd.org/) at the Max Planck Institute of Molecular Plant Physiology constitutes a repository and analysis platform of genomic, transcriptomic, proteomic, and metabolomic plant data provided by the GABI community (Riaño-Pachón et al., 2009). Beside the data, current versions of useful tools are being made accessible via GabiPD, such as MapMan (Usadel et al., 2005) and SATlotyper (Neigenfind et al., 2008). Access to GabiPD is provided via either the web interface or WebServices.In GabiPD, twenty different plant species are currently represented with the model plant A. thaliana on top followed by the crop plants S. tuberosum and H. vulgare. Innovative user interfaces allow interactive access to the different data types, e.g. (i) GreenCards to all text-based information, like sequences and comparative SNP information (e.g., Pajerowska-Mukhtar et al., 2009) (ii) YAMB to comparative genetic maps, (iii) MapManWeb to gene expression or metabolite profiling data mapped onto pathways, or (iv) 2DGelViewer to annotated 2DE gel images. All data types (e.g., clones, protein spots, gene expression data) in GabiPD are pointing to the central Gene GreenCard, where gene information is retrieved from genome annotation projects or UniGene sets (provided by NCBI). With the Gene GreenCards, we provide MapMan and Gene Ontology annotations and ortholog information (currently only between A. thaliana and O. sativa ssp. japonica). Recently, a new graphical representation of transcripts was integrated displaying gene structure (untranslated regions, start and stop codons and exon-exon junctions). Protein domains as well as ESTs, are mapped on the transcript displays. In order to ease the transfer of knowledge from model to crop plants, we have performed similarity-based mappings between closely related species, i.e., O. sativa ssp. japonica and H. vulgare. By the integration of complex data in a framework of existing knowledge, GabiPD provides new insights and allows for new interpretations of plant data.This work is/was supported by the BMBF (GABI grants 0312272, 0313112, 0315046).Neigenfind J et al. (2008) Haplotype inference from unphased SNP data in heterozygous polyploids based on SAT. BMC Genomics 9:356.Pajerowska-Mukhtar K et al. (2009) Single nucleotide polymorphisms in the allene oxide synthase 2 gene are associated with field resistance to late blight in populations of tetraploid potato cultivars. Genetics, doi:10.1534/genetics.108.094268Riano-Pachon DM et al. (2009) GabiPD: The GABI Primary Database – a plant integrative ‘omics’ database. Nucleic Acids Research 37(Database issue):D954-9, DOI 10.1093/nar/gkn611Usadel B et al (2006) PageMan: an interactive ontology tool to generate, display, and annotate overview graphs for profiling experiments. BMC Bioinformatics 7:535. http://dx.doi.org/10.1038/npre.2009.3218.1 Wed, 06 May 2009 20:39:02 UTC The GABI Primary Database: GABIPD – Integration of Plant ‘Omics’-Data in Gene Context doi:10.1038/npre.2009.3218.1 2009-05-06 Birgit Kersten Nature Precedings 2009-05-06T20:39:02Z Poster Genetics & Genomics Bioinformatics Plant Biology http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2009.3169.1 The Protein Ontology (PRO) is designed as a formal and well-principled Open Biomedical Ontologies (OBO) Foundry ontology for proteins. The components of PRO extend from the classification of proteins, on the basis of evolutionary relationships at the homeomorphic level, to the representation of the multiple protein forms of a gene, such as those resulting from alternative splicing, cleavage and/or post-translational modifications. As an ontology, PRO differs from a database in that it provides description about the protein types and their relationships. In this way PRO can be integrated with or cross-referenced by other ontologies and/or databases. The representation of specific protein entities in PRO allows precise definition of objects in pathways, complexes, or in disease modeling. This is useful for proteomics studies where isoforms and modified forms must be differentiated and for biological pathway/network representation where the cascade of events often depends on a specific protein modification. The PRO framework is designed to allow the community to curate any protein entities of interest and will provide a stable unique identifier to any protein type. PRO is manually curated starting with content derived from various data sources coupling with scientific literature. Only annotation with experimental evidence is included, and is in the form of relationship to other ontologies (such as Gene Ontology, Sequence Ontology, and PSI-MOD). We have developed a web-based curation editor for PRO community annotation. In the tutorial, we will first give a brief introduction to the ontology and its relevance to the research communities – OBO ontologies, MOD, pathway and other databases, and any resources that need references/links to protein types. We will show the components of the PRO entry report, and how to search the ontology. Then, we will walk through an example where we will teach the basic curation steps: accessing the web editor, entering the protein to be defined with source attribution, and adding functional annotation. We will provide the necessary tools and documentation so that the user will be able to start curating the protein types of interest. PRO URL: http://pir.georgetown.edu/pro/ http://dx.doi.org/10.1038/npre.2009.3169.1 Fri, 24 Apr 2009 16:16:11 UTC Protein Ontology and Community Curation doi:10.1038/npre.2009.3169.1 2009-04-24 Cecilia Arighi Nature Precedings 2009-04-24T16:16:11Z Presentation Molecular Cell Biology Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2009.3168.1 NISEED (Network for In situ Expression and Embryological Data) is a generic infrastructure for the creation, maintenance and integration of molecular and anatomical information on model organisms. We applied it to ascidians which are marine invertebrate chordates. These animals constitute model organisms of choice for developmental biology because their embryos develop with a small number of cells and an invariant lineage, allowing their study with a cellular level of resolution. In ANISEED (Ascidian NISEED), embryogenesis of ascidian is represented at the level of the genome via functional gene annotations, cis-regulatory elements or gene expression data, at the level of the cell by representing its morphology, fates, lineage, and relations with its neighbors, or at the level of the whole embryo by representing its anatomy and morphogenesis at successive developmental stages. The system provides also tool and standard to enter, annotate, curate and manage data. All results can be accessed through the ANISEED website at http://aniseed-ibdm.univ-mrs.fr http://dx.doi.org/10.1038/npre.2009.3168.1 Fri, 24 Apr 2009 16:14:03 UTC Curation of NISEED, an integrative framework for the digital representation of embryonic development doi:10.1038/npre.2009.3168.1 2009-04-24 Delphine Dauga Nature Precedings 2009-04-24T16:14:03Z Poster Developmental Biology Genetics & Genomics Bioinformatics http://creativecommons.org/licenses/by/3.0/