Database: The Journal of Biological Databases and Curation - RSS feed of current content

New mutant phenotype data curation system in the Saccharomyces Genome Database

Thu, 26 Mar 2009 00:00:00 PDT

The Saccharomyces Genome Database (SGD; http://www.yeastgenome.org/) organizes and displays molecular and genetic information about the genes and proteins of baker's yeast, Saccharomyces cerevisiae. Mutant phenotype screens have been the starting point for a large proportion of yeast molecular biological studies, and are still used today to elucidate the functions of uncharacterized genes and discover new roles for previously studied genes. To greatly facilitate searching and comparison of mutant phenotypes across genes, we have devised a new controlled-vocabulary system for capturing phenotype information. Each phenotype annotation is represented as an ‘observable’, which is the entity, or process that is observed, and a ‘qualifier’ that describes the change in that entity or process in the mutant (e.g. decreased, increased, or abnormal). Additional information about the mutant, such as strain background, allele name, conditions under which the phenotype is observed, or the identity of relevant chemicals, is captured in separate fields. For each gene, a summary of the mutant phenotype information is displayed on the Locus Summary page, and the complete information is displayed in tabular format on the Phenotype Details Page. All of the information is searchable and may also be downloaded in bulk using SGD's Batch Download Tool or Download Data Files Page. In the future, phenotypes will be integrated with other curated data to allow searching across different types of functional information, such as genetic and physical interaction data and Gene Ontology annotations.

Database URL: http://www.yeastgenome.org/

DATABASE: A new forum for biological databases and curation

Landsman, D., Gentleman, R., Kelso, J., Francis Ouellette, B. F. — Thu, 26 Mar 2009 00:00:00 PDT

Analysis of CASP8 targets, predictions and assessment methods

Tue, 28 Apr 2009 00:00:00 PDT

Results of the recent Critical Assessment of Techniques for Protein Structure Prediction, CASP8, present several valuable sources of information. First, CASP targets comprise a realistic sample of currently solved protein structures and exemplify the corresponding challenges for predictors. Second, the plethora of predictions by all possible methods provides an unusually rich material for evolutionary analysis of target proteins. Third, CASP results show the current state of the field and highlight specific problems in both predicting and assessing. Finally, these data can serve as grounds to develop and analyze methods for assessing prediction quality. Here we present results of our analysis in these areas. Our objective is not to duplicate CASP assessment, but to use our unique experience as former CASP5 assessors and CASP8 predictors to (i) offer more insights into CASP targets and predictions based on expert analysis, including invaluable analysis prior to target structure release; and (ii) develop an assessment methodology tailored towards current challenges in the field. Specifically, we discuss preparing target structures for assessment, parsing protein domains, balancing evaluations based on domains and on whole chains, dividing targets into categories and developing new evaluation scores. We also present evolutionary analysis of the most interesting and challenging targets.

Database URL: Our results are available as a comprehensive database of targets and predictions at http://prodata.swmed.edu/CASP8.

The Homeodomain Resource: a comprehensive collection of sequence, structure, interaction, genomic and functional information on the homeodomain protein family

Moreland, R. T., Ryan, J. F., Pan, C., Baxevanis, A. D. — Tue, 28 Apr 2009 00:00:00 PDT

The Homeodomain Resource is a curated collection of sequence, structure, interaction, genomic and functional information on the homeodomain family. The current version builds upon previous versions by the addition of new, complete sets of homeodomain sequences from fully sequenced genomes, the expansion of existing curated homeodomain information and the improvement of data accessibility through better search tools and more complete data integration. This release contains 1534 full-length homeodomain-containing sequences, 93 experimentally derived homeodomain structures, 101 homeodomain protein–protein interactions, 107 homeodomain DNA-binding sites and 206 homeodomain proteins implicated in human genetic disorders.

Database URL: The Homeodomain Resource is freely available and can be accessed at http://research.nhgri.nih.gov/homeodomain/

Gramene QTL database: development, content and applications

Tue, 12 May 2009 10:00:40 PDT

Gramene is a comparative information resource for plants that integrates data across diverse data domains. In this article, we describe the development of a quantitative trait loci (QTL) database and illustrate how it can be used to facilitate both the forward and reverse genetics research. The QTL database contains the largest online collection of rice QTL data in the world. Using flanking markers as anchors, QTLs originally reported on individual genetic maps have been systematically aligned to the rice sequence where they can be searched as standard genomic features. Researchers can determine whether a QTL co-localizes with other QTLs detected in independent experiments and can combine data from multiple studies to improve the resolution of a QTL position. Candidate genes falling within a QTL interval can be identified and their relationship to particular phenotypes can be inferred based on functional annotations provided by ontology terms. Mutations identified in functional genomics populations and association mapping panels can be aligned with QTL regions to facilitate fine mapping and validation of gene–phenotype associations. By assembling and integrating diverse types of data and information across species and levels of biological complexity, the QTL database enhances the potential to understand and utilize QTL information in biological research.

DBH2H: vertebrate head-to-head gene pairs annotated at genomic and post-genomic levels

Yu, H., Yu, F.-D., Zhang, G.-Q., Shen, X., Chen, Y.-Q., Li, Y.-Y., Li, Y.-X. — Tue, 02 Jun 2009 09:57:41 PDT

DBH2H collects head-to-head (h2h) gene pairs identified from human, mouse, rat, chicken and fugu genomes, and distinguishes the ortholog mapping relationship among them. The gene pairs in DBH2H are annotated with sequential features including single nucleotide polymorphisms, CpG islands and transcription factor binding sites, as well as functional terms and genetic disorders. In addition, the expression correlation information based on 117 microarray datasets is included. By providing user-friendly access to these data, DBH2H represents a valuable resource for further analyses of this important gene arrangement in terms of transcriptional regulation mechanisms, evolutionary conservation, disease relevance, etc.

Database URL: http://lifecenter.sgst.cn/h2h/

Radiation Genes: a database devoted to microarrays screenings revealing transcriptome alterations induced by ionizing radiation in mammalian cells

Tue, 28 Jul 2009 09:16:07 PDT

The analysis of the great extent of data generated by using DNA microarrays technologies has shown that the transcriptional response to radiation can be considerably different depending on the quality, the dose range and dose rate of radiation, as well as the timing selected for the analysis. At present, it is very difficult to integrate data obtained under several experimental conditions in different biological systems to reach overall conclusions or build regulatory models which may be tested and validated. In fact, most available data is buried in different websites, public or private, in general or local repositories or in files included in published papers; it is often in various formats, which makes a wide comparison even more difficult. The Radiation Genes Database (http://www.caspur.it/RadiationGenes) collects microarrays data from various local and public repositories or from published papers and supplementary materials. The database classifies it in terms of significant variables, such as radiation quality, dose, dose rate and sampling timing, as to provide user-friendly tools to facilitate data integration and comparison.

miRo: a miRNA knowledge base

Fri, 07 Aug 2009 08:55:41 PDT

miRò is a web-based knowledge base that provides users with miRNA–phenotype associations in humans. It integrates data from various online sources, such as databases of miRNAs, ontologies, diseases and targets, into a unified database equipped with an intuitive and flexible query interface and data mining facilities. The main goal of miRò is the establishment of a knowledge base which allows non-trivial analysis through sophisticated mining techniques and the introduction of a new layer of associations between genes and phenotypes inferred based on miRNAs annotations. Furthermore, a specificity function applied to validated data highlights the most significant associations. The miRò web site is available at: http://ferrolab.dmi.unict.it/miro.

Database URL: http://ferrolab.dmi.unict.it/miro

Dr. Zompo: an online data repository for Zostera marina and Posidonia oceanica ESTs

Tue, 04 Aug 2009 05:32:03 PDT

As ecosystem engineers, seagrasses are angiosperms of paramount ecological importance in shallow shoreline habitats around the globe. Furthermore, the ancestors of independent seagrass lineages have secondarily returned into the sea in separate, independent evolutionary events. Thus, understanding the molecular adaptation of this clade not only makes significant contributions to the field of ecology, but also to principles of parallel evolution as well. With the use of Dr. Zompo, the first interactive seagrass sequence database presented here, new insights into the molecular adaptation of marine environments can be inferred. The database is based on a total of 14 597 ESTs obtained from two seagrass species, Zostera marina and Posidonia oceanica, which have been processed, assembled and comprehensively annotated. Dr. Zompo provides experimentalists with a broad foundation to build experiments and consider challenges associated with the investigation of this class of non-domesticated monocotyledon systems. Our database, based on the Ruby on Rails framework, is rich in features including the retrieval of experimentally determined heat-responsive transcripts, mining for molecular markers (SSRs and SNPs), and weighted key word searches that allow access to annotation gathered on several levels including Pfam domains, GeneOntology and KEGG pathways. Well established plant genome sites such as The Arabidopsis Information Resource (TAIR) and the Rice Genome Annotation Project are interfaced by Dr. Zompo. With this project, we have initialized a valuable resource for plant biologists in general and the seagrass community in particular. The database is expected to grow together with more data to come in the near future, particularly with the recent initiation of the Zostera genome sequencing project.

The Dr. Zompo database is available at http://drzompo.uni-muenster.de/

QuickGO: a user tutorial for the web-based Gene Ontology browser

Huntley, R. P., Binns, D., Dimmer, E., Barrell, D., O'Donovan, C., Apweiler, R. — Tue, 29 Sep 2009 08:13:32 PDT

The Gene Ontology (GO) has proven to be a valuable resource for functional annotation of gene products. At well over 27 000 terms, the descriptiveness of GO has increased rapidly in line with the biological data it represents. Therefore, it is vital to be able to easily and quickly mine the functional information that has been made available through these GO terms being associated with gene products. QuickGO is a fast, web-based tool for browsing the GO and all associated GO annotations provided by the GOA group. After undergoing a redevelopment, QuickGO is now able to offer many more features beyond simple browsing. Users have responded well to the new tool and given very positive feedback about its usefulness. This tutorial will demonstrate how some of these features could be useful to the researcher wanting to discover more about their dataset, particular areas of biology or to find new ways of directing their research.

Database URL: http://www.ebi.ac.uk/QuickGO

The Prion Disease Database: a comprehensive transcriptome resource for systems biology research in prion diseases

Thu, 17 Sep 2009 23:38:56 PDT

Prion diseases reflect conformational conversion of benign isoforms of prion protein (PrP^C) to malignant PrP^Sc isoforms. Networks perturbed by PrP^Sc accumulation and their ties to pathological events are poorly understood. Time-course transcriptomic and phenotypic data in animal models are critical for understanding prion-perturbed networks in systems biology studies. Here, we present the Prion Disease Database (PDDB), the most comprehensive data resource on mouse prion diseases to date. The PDDB contains: (i) time-course mRNA measurements spanning the interval from prion inoculation through appearance of clinical signs in eight mouse strain-prion strain combinations and (ii) histoblots showing temporal PrP^Sc accumulation patterns in brains from each mouse–prion combination. To facilitate prion research, the PDDB also provides a suite of analytical tools for reconstructing dynamic networks via integration of temporal mRNA and interaction data and for analyzing these networks to generate hypotheses.

Database URL: http://prion.systemsbiology.net

A community-curated consensual annotation that is continuously updated: the Bacillus subtilis centred wiki SubtiWiki

Florez, L. A., Roppel, S. F., Schmeisky, A. G., Lammers, C. R., Stulke, J. — Thu, 17 Sep 2009 23:38:56 PDT

Bacillus subtilis is the model organism for Gram-positive bacteria, with a large amount of publications on all aspects of its biology. To facilitate genome annotation and the collection of comprehensive information on B. subtilis, we created SubtiWiki as a community-oriented annotation tool for information retrieval and continuous maintenance. The wiki is focused on the needs and requirements of scientists doing experimental work. This has implications for the design of the interface and for the layout of the individual pages. The pages can be accessed primarily by the gene designations. All pages have a similar flexible structure and provide links to related gene pages in SubtiWiki or to information in the World Wide Web. Each page gives comprehensive information on the gene, the encoded protein or RNA as well as information related to the current investigation of the gene/protein. The wiki has been seeded with information from key publications and from the most relevant general and B. subtilis-specific databases. We think that SubtiWiki might serve as an example for other scientific wikis that are devoted to the genes and proteins of one organism.

Database URL: The wiki can be accessed at http://subtiwiki.uni-goettingen.de/

Differential direct coding: a compression algorithm for nucleotide sequence data

Vey, G. — Thu, 17 Sep 2009 02:54:52 PDT

While modern hardware can provide vast amounts of inexpensive storage for biological databases, the compression of nucleotide sequence data is still of paramount importance in order to facilitate fast search and retrieval operations through a reduction in disk traffic. This issue becomes even more important in light of the recent increase of very large data sets, such as metagenomes. In this article, I propose the Differential Direct Coding algorithm, a general-purpose nucleotide compression protocol that can differentiate between sequence data and auxiliary data by supporting the inclusion of supplementary symbols that are not members of the set of expected nucleotide bases, thereby offering reconciliation between sequence-specific and general-purpose compression strategies. This algorithm permits a sequence to contain a rich lexicon of auxiliary symbols that can represent wildcards, annotation data and special subsequences, such as functional domains or special repeats. In particular, the representation of special subsequences can be incorporated to provide structure-based coding that increases the overall degree of compression. Moreover, supporting a robust set of symbols removes the requirement of wildcard elimination and restoration phases, resulting in a complexity of O(n) for execution time, making this algorithm suitable for very large data sets. Because this algorithm compresses data on the basis of triplets, it is highly amenable to interpretation as a polypeptide at decompression time. Also, an encoded sequence may be further compressed using other existing algorithms, like gzip, thereby maximizing the final degree of compression. Overall, the Differential Direct Coding algorithm can offer a beneficial impact on disk traffic for database queries and other disk-intensive operations.

ORION-VIRCAT: a tool for mapping ICTV and NCBI taxonomies

Valdivia-Granda, W., Larson, F. — Mon, 12 Oct 2009 08:21:11 PDT

Viruses, viroids and prions are the smallest infectious biological entities that depend on their host for replication. The number of pathogenic viruses is considerably large and their impact in human global health is well documented. Currently, the International Committee on the Taxonomy of Viruses (ICTV) has classified ~4379 virus species while the National Center for Biotechnology Information Viral Genomes Resource (NCBI-VGR) database has mapped 617 705 proteins to eight large taxonomic groups. Despite these efforts, an automated approach for mapping the ICTV master list and its officially accepted virus naming to the NCBI-VGR’s taxonomical classification is not available. Due to metagenomic sequencing, it is likely that the discovery and naming of new viral species will increase by at least ten fold. Unfortunately, existing viral databases are not adequately prepared to scale, maintain and annotate automatically ultra-high throughput sequences and place this information into specific taxonomic categories. ORION-VIRCAT is a scalable and interoperable object-relational database designed to serve as a resource for the integration and verification of taxonomical classifications generated by the ICTV and NCBI-VGR. The current release (v1.0) of ORION-VIRCAT is implemented in PostgreSQL and it has been extended to ORACLE, MySQL and SyBase. ORION-VIRCAT automatically mapped and joined 617 705 entries from the NCBI-VGR to the viral naming of the ICTV. This detailed analysis revealed that 399 095 entries from the NCBI-VGR can be mapped to the ICTV classification and that one Order, 10 families, 35 genera and 503 species listed in the ICTV disagree with the the NCBI-VGR classification schema. Nevertheless, we were eable to correct several discrepancies mapping 234 000 additional entries.

Database URL: http://www.orionbiosciences.com/research/orion-vircat.html

A large and accurate collection of peptidase cleavages in the MEROPS database

Rawlings, N. D. — Mon, 02 Nov 2009 04:51:48 PST

Peptidases are enzymes that hydrolyse peptide bonds in proteins and peptides. Peptidases are important in pathological conditions such as Alzheimer's disease, tumour and parasite invasion, and for processing viral polyproteins. The MEROPS database is an Internet resource containing information on peptidases, their substrates and inhibitors. The database now includes details of cleavage positions in substrates, both physiological and non-physiological, natural and synthetic. There are 39 118 cleavages in the collection; including 34 606 from a total of 10 513 different proteins and 2677 cleavages in synthetic substrates. The number of cleavages designated as ‘physiological’ is 13 307. The data are derived from 6095 publications. At least one substrate cleavage is known for 45% of the 2415 different peptidases recognized in the MEROPS database. The website now has three new displays: two showing peptidase specificity as a logo and a frequency matrix, the third showing a dynamically generated alignment between each protein substrate and its most closely related homologues. Many of the proteins described in the literature as peptidase substrates have been studied only in vitro. On the assumption that a physiologically relevant cleavage site would be conserved between species, the conservation of every site in terms of peptidase preference has been examined and a number have been identified that are not conserved. There are a number of cogent reasons why a site might not be conserved. Each poorly conserved site has been examined and a reason postulated. Some sites are identified that are very poorly conserved where cleavage is more likely to be fortuitous than of physiological relevance. This data-set is freely available via the Internet and is a useful training set for algorithms to predict substrates for peptidases and cleavage positions within those substrates. The data may also be useful for the design of inhibitors and for engineering novel specificities into peptidases.

Database URL: http://merops.sanger.ac.uk

Collaborative annotation of genes and proteins between UniProtKB/Swiss-Prot and dictyBase

Thu, 15 Oct 2009 05:24:00 PDT

UniProtKB/Swiss-Prot, a curated protein database, and dictyBase, the Model Organism Database for Dictyostelium discoideum, have established a collaboration to improve data sharing. One of the major steps in this effort was the ‘Dicty annotation marathon’, a week-long exercise with 30 annotators aimed at achieving a major increase in the number of D. discoideum proteins represented in UniProtKB/Swiss-Prot. The marathon led to the annotation of over 1000 D. discoideum proteins in UniProtKB/Swiss-Prot. Concomitantly, there were a large number of updates in dictyBase concerning gene symbols, protein names and gene models. This exercise demonstrates how UniProtKB/Swiss-Prot can work in very close cooperation with model organism databases and how the annotation of proteins can be accelerated through those collaborations.

Models for financial sustainability of biological databases and resources

Fri, 23 Oct 2009 06:44:42 PDT

Following the technological advances that have enabled genome-wide analysis in most model organisms over the last decade, there has been unprecedented growth in genomic and post-genomic science with concomitant generation of an exponentially increasing volume of data and material resources. As a result, numerous repositories have been created to store and archive data, organisms and material, which are of substantial value to the whole community. Sustained access, facilitating re-use of these resources, is essential, not only for validation, but for re-analysis, testing of new hypotheses and developing new technologies/platforms. A common challenge for most data resources and biological repositories today is finding financial support for maintenance and development to best serve the scientific community. In this study we examine the problems that currently confront the data and resource infrastructure underlying the biomedical sciences. We discuss the financial sustainability issues and potential business models that could be adopted by biological resources and consider long term preservation issues within the context of mouse functional genomics efforts in Europe.

Integrating text mining into the MGI biocuration workflow

Dowell, K.G., McAndrews-Hill, M.S., Hill, D.P., Drabkin, H.J., Blake, J.A. — Fri, 20 Nov 2009 22:34:56 PST

A major challenge for functional and comparative genomics resource development is the extraction of data from the biomedical literature. Although text mining for biological data is an active research field, few applications have been integrated into production literature curation systems such as those of the model organism databases (MODs). Not only are most available biological natural language (bioNLP) and information retrieval and extraction solutions difficult to adapt to existing MOD curation workflows, but many also have high error rates or are unable to process documents available in those formats preferred by scientific journals.

In September 2008, Mouse Genome Informatics (MGI) at The Jackson Laboratory initiated a search for dictionary-based text mining tools that we could integrate into our biocuration workflow. MGI has rigorous document triage and annotation procedures designed to identify appropriate articles about mouse genetics and genome biology. We currently screen ~1000 journal articles a month for Gene Ontology terms, gene mapping, gene expression, phenotype data and other key biological information. Although we do not foresee that curation tasks will ever be fully automated, we are eager to implement named entity recognition (NER) tools for gene tagging that can help streamline our curation workflow and simplify gene indexing tasks within the MGI system. Gene indexing is an MGI-specific curation function that involves identifying which mouse genes are being studied in an article, then associating the appropriate gene symbols with the article reference number in the MGI database.

Here, we discuss our search process, performance metrics and success criteria, and how we identified a short list of potential text mining tools for further evaluation. We provide an overview of our pilot projects with NCBO's Open Biomedical Annotator and Fraunhofer SCAI's ProMiner. In doing so, we prove the potential for the further incorporation of semi-automated processes into the curation of the biomedical literature.