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At least 1,531 records · Page 85Linked to original sources
PubMed1997

A comparison of expressed sequence tags (ESTs) to human genomic sequences.

The Expressed Sequence Tag (EST) division of GenBank, dbEST, is a large repository of the data being generated by human genome sequencing centers. ESTs are short, single pass cDNA sequences generated from randomly selected library clones. The approximately 415 000 human ESTs represent a valuable, low priced, and easily accessible biological reagent. As many ESTs are derived from yet uncharacterized genes, dbEST is a prime starting point for the identification of novel mRNAs. Conversely, other genes are represented by hundreds of ESTs, a redundancy which may provide data about rare mRNA isoforms. Here we present an analysis of >1000 ESTs generated by the WashU-Merck EST project. These ESTs were collected by querying dbEST with the genomic sequences of 15 human genes. When we aligned the matching ESTs to the genomic sequences, we found that in one gene, 73% of the ESTs which derive from spliced or partially spliced transcripts either contain intron sequences or are spliced at previously unreported sites; other genes have lower percentages of such ESTs, and some have none. This finding suggests that ESTs could provide researchers with novel information about alternative splicing in certain genes. In a related analysis of pairs of ESTs which are reported to derive from a single gene, we found that as many as 26% of the pairs do not BOTH align with the sequence of the same gene. We suspect that some of these unusual ESTs result from artifacts in EST generation, and caution researchers that they may find such clones while analyzing sequences in dbEST.

Alternative Splicing↗
PubMed1998

IXDB, an X chromosome integrated database.

The integrated X chromosome database (IXDB) is a repository for physical mapping data of the human X chromosome. Its current content is the result of a strict integration of data stemming from many different sources. The main features of IXDB include a flexible and extendible schema, a comfortable and fully cross-referenced WWW interface (http://ixdb.mpimg-berlin-dahlem.mpg.de ) and a graphical map viewer implemented in JAVA. The database stores objects used in physical mapping as well as the maps resulting from this work, but a strong emphasis is placed on recording experiments that connect objects together. This should greatly contribute to fulfilling one of the major goals of the database: to support the construction of an integrated physical, genetic, transcript and sequence map of the human X chromosome.

Chromosome Mapping↗
PubMed1998

GDB: the Human Genome Database.

The Genome Database (GDB, http://www.gdb.org ) is a public repository of data on human genes, clones, STSs, polymorphisms and maps. GDB entries are highly cross-linked to each other, to literature citations and to entries in other databases, including the sequence databases, OMIM, and the Mouse Genome Database. Mapping data from large genome centers and smaller mapping efforts are added to GDB on an ongoing basis. The database can be searched by a variety of methods, ranging from keyword searches to complex queries. Major functionality extensions in the last year include the ongoing computation of integrated human genome maps, called Comprehensive Maps, and the use of those maps to support positional queries and graphic displays. The capabilities of the GDB map viewer (Mapview) have been extended to include map printing and the graphical display of ad hoc query results. The HUGO Nomenclature Committee continues to curate the proposed and official gene symbols and related data in collaboration with GDB. As genome research shifts its emphasis from mapping to sequencing and functional analysis, the scope of the GDB schema is being extended. We are in the process of adding representations of gene function and expression, and improving our representation of human polymorphism and mutation.

Animals↗
PubMed1999

The ENZYME data bank in 1999.

The ENZYME data bank is a repository of information related to the nomenclature of enzymes. In recent years it has become an indispensable resource for the development of metabolic databases. The current version contains information on 3704 enzymes. It is available through the ExPASy WWW server (http://www.expasy.ch/).

Databases, Factual↗
PubMed1999

The Enhanced Microbial Genomes Library.

Since the obtention of the complete sequence of Haemophilus influenzae Rd in 1995, the number of bacterial genomes entirely sequenced has regularly increased. A problem is that the quality of the annotations of these very large sequences is usually lower than those of the shorter entries encountered in the repository collections. Moreover, classical sequence database management systems have difficulties in handling entries of that size. In this context, we have decided to build the Enhanced Microbial Genomes Library (EMGLib) in which these two problems are alleviated. This library contains all the complete genomes from bacteria already sequenced and the yeast genome in GenBank format. The annotations are improved by the introduction of data on codon usage, gene orientation on the chromosome and gene families. It is possible to access EMGLib through two database systems set up on World Wide Web servers: the PBIL server at http://pbil.univ-lyon1.fr/emglib/emglib. html and the MICADO server at http://locus.jouy.inra.fr/micado

Base Sequence↗
PubMed2000

The ENZYME database in 2000.

The ENZYME database is a repository of information related to the nomenclature of enzymes. In recent years it has became an indispensable resource for the development of metabolic databases. The current version contains information on 3705 enzymes. It is available through the ExPASy WWW server (http://www.expasy.ch/enzyme/ ).

Databases, Factual↗
PubMed2000

EMGLib: the enhanced microbial genomes library (update 2000).

As the number of complete microbial genomes publicly available is still growing, the problem of annotation quality in these very large sequences remains unsolved. Indeed, the number of annotations associated with complete genomes is usually lower than those of the shorter entries encountered in the repository collections. Moreover, classical sequence database management systems have difficulties in handling entries of such size. In this context, the Enhanced Microbial Genomes Library (EMGLib) was developed to try to alleviate these problems. This library contains all the complete genomes from prokaryotes (bacteria and archaea) already sequenced and the yeast genome in GenBank format. The annotations are improved by the introduction of data on codon usage, gene orientation on the chromosome and gene families. It is possible to access EMGLib through two database systems set up on WWW servers: the PBIL server at http://pbil.univ-lyon1.fr/emglib.html and the MICADO server at http://locus.jouy.inra.fr/micado

Base Sequence↗
PubMed2000

CyanoBase, the genome database for Synechocystis sp. strain PCC6803: status for the year 2000.

CyanoBase provides an online resource for access to data on genomic information about the cyanobacterium Synechocystis sp. strain PCC6803. The database contains annotations for each protein-coding gene deduced from the entire nucleotide sequence of the genome, gene classification lists, and keyword and similarity search engines. Core portions of CyanoBase consist of annotations for each of the 3168 protein genes deduced from the entire nucleotide sequence of this genome. The contents of each gene were improved by updating with the results of similarity searches and by introducing references for analysis in bioinformatics. The database now contains repository facilities that store and provide experimental information, in addition to providing proposals for the function of each gene. This information should help to avoid unnecessary, overlapping experiments and should assist communication between scientists who wish to elucidate the function of putative genes on the cyanobacteria genome. The current URL of CyanoBase is http://www.kazusa.or.jp:8080/cyano/

Cyanobacteria↗
PubMed2000

The phytophthora genome initiative database: informatics and analysis for distributed pathogenomic research.

The Phytophthora Genome Initiative (PGI) is a distributed collaboration to study the genome and evolution of a particularly destructive group of plant pathogenic oomycete, with the goal of understanding the mechanisms of infection and resistance. NCGR provides informatics support for the collaboration as well as a centralized data repository. In the pilot phase of the project, several investigators prepared Phytophthora infestans and Phytophthora sojae EST and Phytophthora sojae BAC libraries and sent them to another laboratory for sequencing. Data from sequencing reactions were transferred to NCGR for analysis and curation. An analysis pipeline transforms raw data by performing simple analyses (i.e., vector removal and similarity searching) that are stored and can be retrieved by investigators using a web browser. Here we describe the database and access tools, provide an overview of the data therein and outline future plans. This resource has provided a unique opportunity for the distributed, collaborative study of a genus from which relatively little sequence data are available. Results may lead to insight into how better to control these pathogens. The homepage of PGI can be accessed at http:www.ncgr.org/pgi, with database access through the database access hyperlink.

Databases, Factual↗
PubMed2000

Gene discovery using the maize genome database ZmDB.

Zea mays DataBase (ZmDB) is a repository and analysis tool for sequence, expression and phenotype data of the major crop plant maize. The data accessible in ZmDB are mostly generated in a large collaborative project of maize gene discovery, sequencing and phenotypic analysis using a transposon tagging strategy and expressed sequence tag (EST) sequencing. ESTs constitute most of the current content. Database search tools, convenient links to external databases, and novel sequence analysis programs for spliced alignment are provided and together serve as an efficient protocol for gene discovery by sequence inspection. ZmDB can be accessed at http://zmdb. iastate.edu. ZmDB also provides web-based ordering of materials generated in the project, including EST and genomic DNA clones, seeds of mutant plants and microarrays of amplified EST and genomic DNA sequences.

Amino Acid Sequence↗
PubMed2000

INE: a rice genome database with an integrated map view.

The Rice Genome Research Program (RGP) launched a large-scale rice genome sequencing in 1998 aimed at decoding all genetic information in rice. A new genome database called INE (INtegrated rice genome Explorer) has been developed in order to integrate all the genomic information that has been accumulated so far and to correlate these data with the genome sequence. A web interface based on Java applet provides a rapid viewing capability in the database. The first operational version of the database has been completed which includes a genetic map, a physical map using YAC (Yeast Artificial Chromosome) clones and PAC (P1-derived Artificial Chromosome) contigs. These maps are displayed graphically so that the positional relationships among the mapped markers on each chromosome can be easily resolved. INE incorporates the sequences and annotations of the PAC contig. A site on low quality information ensures that all submitted sequence data comply with the standard for accuracy. As a repository of rice genome sequence, INE will also serve as a common database of all sequence data obtained by collaborating members of the International Rice Genome Sequencing Project (IRGSP). The database can be accessed at http://www. dna.affrc.go.jp:82/giot/INE. html or its mirror site at http://www.staff.or.jp/giot/INE.html

Chromosomes, Artificial, Yeast↗
PubMed2001

The ARKdb: genome databases for farmed and other animals.

The ARKdb genome databases provide comprehensive public repositories for genome mapping data from farmed species and other animals (http://www.thearkdb.org) providing a resource similar in function to that offered by GDB or MGD for human or mouse genome mapping data, respectively. Because we have attempted to build a generic mapping database, the system has wide utility, particularly for those species for which development of a specific resource would be prohibitive. The ARKdb genome database model has been implemented for 10 species to date. These are pig, chicken, sheep, cattle, horse, deer, tilapia, cat, turkey and salmon. Access to the ARKdb databases is effected via the World Wide Web using the ARKdb browser and Anubis map viewer. The information stored includes details of loci, maps, experimental methods and the source references. Links to other information sources such as PubMed and EMBL/GenBank are provided. Responsibility for data entry and curation is shared amongst scientists active in genome research in the species of interest. Mirror sites in the United States are maintained in addition to the central genome server at Roslin.

Animals↗
PubMed2001

GenMapDB: a database of mapped human BAC clones.

GenMapDB (http://genomics.med.upenn.edu/genmapdb) is a repository of human bacterial artificial chromosome (BAC) clones mapped by our laboratory to sequence-tagged site markers. Currently, GenMapDB contains over 3000 mapped clones that span 19 chromosomes, chromosomes 2, 4, 5, 9-22, X and Y. This database provides positional information about human BAC clones from the RPCI-11 human male BAC library. It also contains restriction fragment analysis data and end sequences of the clones. GenMapDB is freely available to the public. The main purpose of GenMapDB is to organize the mapping data and to allow the research community to search for mapped BAC clones that can be used in gene mapping studies and chromosomal mutation analysis projects.

Chromosome Mapping↗
PubMed2001

LGICdb: the ligand-gated ion channel database.

Ligand-Gated Ion Channels (LGIC) are polymeric transmembrane proteins involved in the fast response to numerous neurotransmitters. All these receptors are formed by homologous subunits and the last two decades revealed an unexpected wealth of genes coding for these subunits. The Ligand-Gated Ion Channel database (LGICdb) has been developed to handle this increasing amount of data. The database aims to provide only one entry for each gene, containing annotated nucleic acid and protein sequences. The repository is carefully structured and the entries can be retrieved by various criteria. In addition to the sequences, the LGICdb provides multiple sequence alignments, phylogenetic analyses and atomic coordinates when available. The database is accessible via the World Wide Web (http://www.pasteur.fr/recherche/banques/LGIC /LGIC.html), where it is continuously updated. The version 16 (September 2000) available for download contained 333 entries covering 34 species.

Databases, Factual↗
PubMed2001

The life sciences Global Image Database (GID).

Although a vast amount of life sciences data is generated in the form of images, most scientists still store images on extremely diverse and often incompatible storage media, without any type of metadata structure, and thus with no standard facility with which to conduct searches or analyses. Here we present a solution to unlock the value of scientific images. The Global Image Database (GID) is a web-based (http://www.gwer.ch/qv/gid/gid.ht m ) structured central repository for scientific annotated images. The GID was designed to manage images from a wide spectrum of imaging domains ranging from microscopy to automated screening. The annotations in the GID define the source experiment of the images by describing who the authors of the experiment are, when the images were created, the biological origin of the experimental sample and how the sample was processed for visualization. A collection of experimental imaging protocols provides details of the sample preparation, and labeling, or visualization procedures. In addition, the entries in the GID reference these imaging protocols with the probe sequences or antibody names used in labeling experiments. The GID annotations are searchable by field or globally. The query results are first shown as image thumbnail previews, enabling quick browsing prior to original-sized annotated image retrieval. The development of the GID continues, aiming at facilitating the management and exchange of image data in the scientific community, and at creating new query tools for mining image data.

Biological Science Disciplines↗
PubMed2001

SPINE: an integrated tracking database and data mining approach for identifying feasible targets in high-throughput structural proteomics.

High-throughput structural proteomics is expected to generate considerable amounts of data on the progress of structure determination for many proteins. For each protein this includes information about cloning, expression, purification, biophysical characterization and structure determination via NMR spectroscopy or X-ray crystallography. It will be essential to develop specifications and ontologies for standardizing this information to make it amenable to retrospective analysis. To this end we created the SPINE database and analysis system for the Northeast Structural Genomics Consortium. SPINE, which is available at bioinfo.mbb.yale.edu/nesg or nesg.org, is specifically designed to enable distributed scientific collaboration via the Internet. It was designed not just as an information repository but as an active vehicle to standardize proteomics data in a form that would enable systematic data mining. The system features an intuitive user interface for interactive retrieval and modification of expression construct data, query forms designed to track global project progress and external links to many other resources. Currently the database contains experimental data on 985 constructs, of which 740 are drawn from Methanobacterium thermoautotrophicum, 123 from Saccharomyces cerevisiae, 93 from Caenorhabditis elegans and the remainder from other organisms. We developed a comprehensive set of data mining features for each protein, including several related to experimental progress (e.g. expression level, solubility and crystallization) and 42 based on the underlying protein sequence (e.g. amino acid composition, secondary structure and occurrence of low complexity regions). We demonstrate in detail the application of a particular machine learning approach, decision trees, to the tasks of predicting a protein's solubility and propensity to crystallize based on sequence features. We are able to extract a number of key rules from our trees, in particular that soluble proteins tend to have significantly more acidic residues and fewer hydrophobic stretches than insoluble ones. One of the characteristics of proteomics data sets, currently and in the foreseeable future, is their intermediate size ( approximately 500-5000 data points). This creates a number of issues in relation to error estimation. Initially we estimate the overall error in our trees based on standard cross-validation. However, this leaves out a significant fraction of the data in model construction and does not give error estimates on individual rules. Therefore, we present alternative methods to estimate the error in particular rules.

Animals↗
PubMed2002

JSNP: a database of common gene variations in the Japanese population.

JSNP is a repository of Japanese Single Nucleotide Polymorphism (SNP) data, begun in 2000 and developed through the Prime Minister's Millennium Project. The aim of this undertaking is to identify and collate up to 150 000 SNPs from the Japanese population, located in genes or in adjacent regions that might influence the coding sequence of the genes. The project has been carried out by a collaboration between the Human Genome Center (HGC) in the Institute of Medical Science (IMS) at the University of Tokyo and the Japan Science and Technology Corporation (JST). JSNP serves as both a storage site for the Japanese SNPs obtained from the ongoing project and as a facility for public dissemination to allow researchers access to high quality SNP data. A primary motivation of the project is the construction of a basic data set to identify relationships between polymorphisms and common diseases or the reaction to drugs. As such, emphasis has been placed on the identification of SNPs that lie in candidate regions which may affect phenotype but which would not necessarily directly cause disease. Unrestricted access to JSNP and any associated files is available at http://snp.ims.u-tokyo.ac.jp/.

Chromosomes, Human↗
PubMed2002

HugeIndex: a database with visualization tools for high-density oligonucleotide array data from normal human tissues.

High-density oligonucleotide arrays are a powerful tool for uncovering changes in global gene expression in various disease states. To this end, it is essential to first characterize the variations of gene expression in normal physiological processes. We established the Human Gene Expression (HuGE) Index database (www.HugeIndex.org) to serve as a public repository for gene expression data on normal human tissues using high-density oligonucleotide arrays. This resource currently contains the results of 59 gene expression experiments on 19 human tissues. We provide interactive tools for researchers to query and visualize our data over the Internet. To facilitate data analysis, we cross-reference each gene on the array with its annotation in the LocusLink database at NCBI.

Computer Graphics↗