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Maintaining patient confidentiality in the public domain Internet Autopsy Database (IAD).

The Internet provides the opportunity of permitting public access to large databases containing patient information that can be shared and utilized by epidemiologists, health planners, and medical researchers. Until now, large databases containing patient information have been held in strict confidence, with database access available only to approved researchers or to researchers with access limited to only specific portions of the database. The Internet Autopsy Database (IAD) consists of demographic and pathologic data from over 49,000 autopsies contributed by over a dozen academic medical institutions. Each autopsy record in the public database consists of a uniform set of demographics and SNOMED-compatible terms. To make the database publicly available, a strategy had to be devised that assured the privacy of every person included in the database. A key step involved translating the autopsy facesheets into a listing of SNOMED-compatible terms that effectively eliminated identifying terminology, replacing free text with a generic nomenclature that preserves diagnostic information. The entire database is available on the Internet at: http:@www.med.jhu.edu/pathology/iad.html

Autopsy↗

Use of large databases for resolving critical care problems.

Large databases allow for rapid access to large volumes of data. To convert raw data to information, large numbers of data points must be correlated into a descriptive pattern that can be interpreted by the user. Databases must be constructed so as to allow reliable extraction of the raw data into a format that supports analysis of events in a meaningful, objective, and reproducible manner. Databases must be responsive to a variety of users. They must not demand unrealistic amounts of effort on those responsible for data entry. Standard protocols in various stages of development will make databases easier to use and more reliable. Database management tools such as the Internet and the National Library of Medicine will become more integrated into the practice of critical care medicine at all levels, including administration, clinical care, and research. This article provides an overview of the capabilities and difficulties associated with large databases. The major areas of use of large databases in the hospital setting are administration, bibliographic, patient care, research, and education. Each of these areas has different requirements and is supported by different types of databases. The advantages and disadvantages of linear, relational, and object-oriented databases are discussed. Issues relating to methods of data entry and the accuracy and reliability of data are discussed. The challenges involving integration of various sources of data and the interfacing of devices are reviewed.

Critical Care↗

AraCyc: a biochemical pathway database for Arabidopsis.

AraCyc is a database containing biochemical pathways of Arabidopsis, developed at The Arabidopsis Information Resource (http://www.arabidopsis.org). The aim of AraCyc is to represent Arabidopsis metabolism as completely as possible with a user-friendly Web-based interface. It presently features more than 170 pathways that include information on compounds, intermediates, cofactors, reactions, genes, proteins, and protein subcellular locations. The database uses Pathway Tools software, which allows the users to visualize a bird's eye view of all pathways in the database down to the individual chemical structures of the compounds. The database was built using Pathway Tools' Pathologic module with MetaCyc, a collection of pathways from more than 150 species, as a reference database. This initial build was manually refined and annotated. More than 20 plant-specific pathways, including carotenoid, brassinosteroid, and gibberellin biosyntheses have been added from the literature. A list of more than 40 plant pathways will be added in the coming months. The quality of the initial, automatic build of the database was compared with the manually improved version, and with EcoCyc, an Escherichia coli database using the same software system that has been manually annotated for many years. In addition, a Perl interface, PerlCyc, was developed that allows programmers to access Pathway Tools databases from the popular Perl language. AraCyc is available at the tools section of The Arabidopsis Information Resource Web site (http://www.arabidopsis.org/tools/aracyc).

Arabidopsis↗

Exploring performance issues for a clinical database organized using an entity-attribute-value representation.

BACKGROUND: The entity-attribute-value representation with classes and relationships (EAV/CR) provides a flexible and simple database schema to store heterogeneous biomedical data. In certain circumstances, however, the EAV/CR model is known to retrieve data less efficiently than conventionally based database schemas. OBJECTIVE: To perform a pilot study that systematically quantifies performance differences for database queries directed at real-world microbiology data modeled with EAV/CR and conventional representations, and to explore the relative merits of different EAV/CR query implementation strategies. METHODS: Clinical microbiology data obtained over a ten-year period were stored using both database models. Query execution times were compared for four clinically oriented attribute-centered and entity-centered queries operating under varying conditions of database size and system memory. The performance characteristics of three different EAV/CR query strategies were also examined. RESULTS: Performance was similar for entity-centered queries in the two database models. Performance in the EAV/CR model was approximately three to five times less efficient than its conventional counterpart for attribute-centered queries. The differences in query efficiency became slightly greater as database size increased, although they were reduced with the addition of system memory. The authors found that EAV/CR queries formulated using multiple, simple SQL statements executed in batch were more efficient than single, large SQL statements. CONCLUSION: This paper describes a pilot project to explore issues in and compare query performance for EAV/CR and conventional database representations. Although attribute-centered queries were less efficient in the EAV/CR model, these inefficiencies may be addressable, at least in part, by the use of more powerful hardware or more memory, or both.

Database Management Systems↗

[The application of human mutation databases].

Researches on genome mutation are becoming more and more important with the finish of human genome DNA draft. This review is to classify the existing human mutation databases, including mutation database, SNP(single nucleotide polymorphisms) databases, mutation databases about disease, mutation databases about proteins, mutation databases about map and mutation information about specific gene. We also give advice on how to utilize these mutation databases, and discuss problems of existing databases.

Databases, Factual↗

Maintenance of a nutrient database for clinical trials.

Maintenance of a nutrient database for use in dietary analysis for clinical trials and other medical research studies is described. The database, maintained at the University of Minnesota's Nutrition Coordinating Center (NCC), has been used to calculate dietary intake data for a wide range of diet-disease related investigations including studies on cardiovascular disease, hypertension, cancer, gastroenterology, and osteoporosis. Potential sources of error associated with nutrient databases are identified. Criteria are provided for the selection of a nutrient database to meet study objectives and to minimize the potential for errors and inconsistencies. NCC database maintenance procedures, designed to provide updated and verified nutrient calculations for clinical research, involve adherence to standardized procedures for all aspects of database maintenance including data selection, imputations, quality control, recipe calculations, and documentation. By maintaining multiple versions of the database, the NCC is able to update and expand a working version of the database while providing database stability for individual research studies.

Clinical Trials as Topic↗

An assessment of data quality in the Vermont-Oxford Trials Network database.

The Vermont-Oxford Trials Network is a voluntary collaborative research group of neonatologists that maintains a database for very low birthweight infants (501-1500 g). The database (1) provides core data for randomized trials, (2) serves as a resource for outcomes research in neonatology, and (3) generates quality management reports for participating sites. To assess the reliability of this database and to determine the sources of error, we reviewed 635 medical records chosen at random from among the 4341 eligible infants born at 40 participating data generating sites during an 18-month period beginning January 1, 1990. The estimated frequencies of disagreement between the medical record and database for each of the 10 data items studied and the standard errors of the estimates (in parentheses) were: date of birth 1.3% (0.4), date of admission 2.5% (0.6), date of discharge 8.8% (1.0), birthweight (difference > 50 g) 2.9% (0.6), location of birth (inborn or outborn) 2.1% (0.5), multiple birth 2.2% (0.5), cesarean section 2.5% (0.6), gender 2.1% (0.5), status 28 days after birth 3.4% (0.6), final status 2.9% (0.6). The overall proportions and mean values for items in the database were close to the estimated values based on the random sample of records. There were a total of 247 disagreements between the database and the medical records in the sample. Twenty-three were due to data keying errors. Two hundred twenty-four were due to errors in transcription or interpretation. The rate of data keying errors decreased from over 50 errors per 10,000 fields to less than 15 errors per 10,000 fields when specific quality control procedures, including visual inspection, were instituted. Data keying errors accounted for 13.7% of all disagreements between the database and medical record before improved data entry methods were introduced, and only 3.7% of all errors after they were introduced. We concluded that the Vermont-Oxford Trials Network Database is reliable. Data keying errors have been reduced by the introduction of additional quality control measures. Further reductions in database errors will require measures aimed at minimizing transcription or interpretation errors by individuals completing the data forms.

Computer Communication Networks↗

Construction of validated, non-redundant composite protein sequence databases.

A strategy has been developed for the construction of a validated, comprehensive composite protein sequence database. Entries are amalgamated from primary source data bases by a largely automated set of processes in which redundant and trivially different entries are eliminated. A modular approach has been adopted to allow scientific judgement to be used at each stage of database processing and amalgamation. Source databases are assigned a priority depending on the quality of sequence validation and commenting. Rejection of entries from the lower priority database, in each pairwise comparison of databases, is carried out according to optionally defined redundancy criteria based on sequence segment mismatches. Efficient algorithms for this methodology are embodied in the COMPO software system. COMPO has been applied for over 2 years in construction and regular updating of the OWL composite protein sequence database from the source databases NBRF-PIR, SWISS-PROT, a GenBank translation retrieved from the feature tables, NBRF-NEW, NEWAT86, PSD-KYOTO and the sequences contained in the Brookhaven protein structure databank. OWL is part of the ISIS integrated data resource of protein sequence and structure [Akrigg et al. (1988) Nature, 335, 745-746]. The modular nature of the integration process greatly facilitates the frequent updating of OWL following releases of the source databases. The extent of redundancy in these sources is revealed by the comparison process. The advantages of a robust composite database for sequence similarity searching and information retrieval are discussed.

Amino Acid Sequence↗

Uses of clinical databases.

Clinical databases consist of observational data collected on patients who meet specific criteria. The uses of these databases depend on whether the observations are drawn from a single institution, multiple clinical centers, or are population-based. Single institution databases frequently are used to profile patient accrual. In cases of rare diseases or unusual procedures, multicenter databases are required to amass sufficient information for study. Multicenter databases can be used to address issues related to intercenter variation and to develop statistical models to predict outcome based on prognostic factors. Population-based databases are required to assess incidence, prevalence, and mortality rates of disease. Although the inferences that can be drawn from observational data are limited by selection bias, clinical databases are valuable tools in planning clinical research. Clearly, however, resources are required to develop and maintain clinical databases. In an era when much research funding is directed at hypothesis-driven research, the importance of these clinical databases in developing clinical research hypotheses should not be overlooked.

Information Systems↗

GeneKeyDB: a lightweight, gene-centric, relational database to support data mining environments.

BACKGROUND: The analysis of biological data is greatly enhanced by existing or emerging databases. Most existing databases, with few exceptions are not designed to easily support large scale computational analysis, but rather offer exclusively a web interface to the resource. We have recognized the growing need for a database which can be used successfully as a backend to computational analysis tools and pipelines. Such database should be sufficiently versatile to allow easy system integration. RESULTS: GeneKeyDB is a gene-centered relational database developed to enhance data mining in biological data sets. The system provides an underlying data layer for computational analysis tools and visualization tools. GeneKeyDB relies primarily on existing database identifiers derived from community databases (NCBI, GO, Ensembl, et al.) as well as the known relationships among those identifiers. It is a lightweight, portable, and extensible platform for integration with computational tools and analysis environments. CONCLUSION: GeneKeyDB can enable analysis tools and users to manipulate the intersections, unions, and differences among different data sets.

Algorithms↗

Heterogeneous database integration in biomedicine.

The rapid expansion of biomedical knowledge, reduction in computing costs, and spread of internet access have created an ocean of electronic data. The decentralized nature of our scientific community and healthcare system, however, has resulted in a patchwork of diverse, or heterogeneous, database implementations, making access to and aggregation of data across databases very difficult. The database heterogeneity problem applies equally to clinical data describing individual patients and biological data characterizing our genome. Specifically, databases are highly heterogeneous with respect to the data models they employ, the data schemas they specify, the query languages they support, and the terminologies they recognize. Heterogeneous database systems attempt to unify disparate databases by providing uniform conceptual schemas that resolve representational heterogeneities, and by providing querying capabilities that aggregate and integrate distributed data. Research in this area has applied a variety of database and knowledge-based techniques, including semantic data modeling, ontology definition, query translation, query optimization, and terminology mapping. Existing systems have addressed heterogeneous database integration in the realms of molecular biology, hospital information systems, and application portability.

Computational Biology↗

A strategy for database interoperation.

To realize the full potential of biological databases (DBs) requires more than the interactive, hypertext flavor of database interoperation that is now so popular in the bioinformatics community. Interoperation based on declarative queries to multiple network-accessible databases will support analyses and investigations that are orders of magnitude faster and more powerful than what can be accomplished through interactive navigation. I present a vision of the capabilities that a query-based interoperation infrastructure should provide, and identify assumptions underlying, and requirements of, this vision. I then propose an architecture for query-based interoperation that includes a number of novel components of an information infrastructure for molecular biology. These components include a knowledge base that describes relationships among the conceptualizations used in different biological databases, a module that can determine the DBs that are relevant to a particular query, a module that can translate a query and its results from one conceptualization to another, a collection of DB drivers that provide uniform physical access to different database management systems, a suite of translators that can interconvert among different database schema languages, and a database that describes the network location and access methods for biological databases. A number of the components are translators that bridge the heterogeneities that exist between biological DBs at several different levels, including the conceptual level, the data model, the query language, and data formats.

Artificial Intelligence↗

CoPS: Comprehensive Peptide Signature database.

UNLABELLED: We present the development of a Comprehensive database of 12 076 invariant Peptide Signatures (CoPS) derived from 52 bacterial genomes with a minimum occurrence in at least seven organisms. These peptides were observed in functionally similar proteins and are distributed over nearly 1250 different functional proteins. The database provides function, structure and occurrence in biochemical pathways of the proteins containing these signature peptides. It houses additional information on the signature peptides, such as identical match in other motif/pattern (e.g. PROSITE, BLOCKS, PRINTS and Pfam) databases and the database of interacting proteins, human proteome and mutation effect on these signature peptides. There is a wide applicability of this database in the identification of critical functional residues in proteins. The database also facilitates the identification of folding nucleus/structural determinants in proteins and functional assignment to yet unknown proteins. We demonstrate functional assignment to 2605 hypothetical proteins in bacterial genomes and 112 unknown proteins in human using this database. AVAILABILITY: The database can be freely accessed through the following URL: http://203.195.151.46/copsv2/index.html or http://203.90.127.70/copsv2/index.html

Bacterial Proteins↗

IPD--the Immuno Polymorphism Database.

The Immuno Polymorphism Database (IPD) (http://www.ebi.ac.uk/ipd/) is a set of specialist databases related to the study of polymorphic genes in the immune system. IPD currently consists of four databases: IPD-KIR, contains the allelic sequences of Killer-cell Immunoglobulin-like Receptors; IPD-MHC, a database of sequences of the Major Histocompatibility Complex of different species; IPD-HPA, alloantigens expressed only on platelets; and IPD-ESTAB, which provides access to the European Searchable Tumour Cell-Line Database, a cell bank of immunologically characterized melanoma cell lines. The IPD project works with specialist groups or nomenclature committees who provide and curate individual sections before they are submitted to IPD for online publication. The IPD project stores all the data in a set of related databases. Those sections with similar data, such as IPD-KIR and IPD-MHC share the same database structure. The sharing of a common database structure makes it easier to implement common tools for data submission and retrieval. The data are currently available online from the website and ftp directory; files will also be made available in different formats to download from the website and ftp server. The data will also be included in SRS, BLAST and FASTA search engines at the European Bioinformatics Institute.

Animals↗

Efficiency of database search for identification of mutated and modified proteins via mass spectrometry.

Although protein identification by matching tandem mass spectra (MS/MS) against protein databases is a widespread tool in mass spectrometry, the question about reliability of such searches remains open. Absence of rigorous significance scores in MS/MS database search makes it difficult to discard random database hits and may lead to erroneous protein identification, particularly in the case of mutated or post-translationally modified peptides. This problem is especially important for high-throughput MS/MS projects when the possibility of expert analysis is limited. Thus, algorithms that sort out reliable database hits from unreliable ones and identify mutated and modified peptides are sought. Most MS/MS database search algorithms rely on variations of the Shared Peaks Count approach that scores pairs of spectra by the peaks (masses) they have in common. Although this approach proved to be useful, it has a high error rate in identification of mutated and modified peptides. We describe new MS/MS database search tools, MS-CONVOLUTION and MS-ALIGNMENT, which implement the spectral convolution and spectral alignment approaches to peptide identification. We further analyze these approaches to identification of modified peptides and demonstrate their advantages over the Shared Peaks Count. We also use the spectral alignment approach as a filter in a new database search algorithm that reliably identifies peptides differing by up to two mutations/modifications from a peptide in a database.

Algorithms↗

A searchable database for proteomes of oral microorganisms.

An online database of proteomes for two-dimensional electrophoresis (2DE) gel data was constructed and it is now freely accessible through a web-based interface. Proteins from three oral bacteria, Streptococcus mutans UA159, Actinobacillus actinomycetemcomitans HK1651, and Porphyromonas gingivalis W83, whose genome databases are freely available, were separated by 2DE, and protein spots were analyzed by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) and identified. About 1000 spots from the gels of P. gingivalis W83 were extracted and analyzed by MALDI-TOF, and 330 proteins were identified. In addition, 160 of 240 spots of A. actinomycetemcomitans and 158 of 356 spots of S. mutans were identified. Information such as spot coordinates on the gels, protein names (predicted functions), molecular weights, isoelectroric points, and links to online databases, including Oral Pathogen Sequence Databases of the Los Alamos National Laboratory Bioscience Division (ORALGEN) and National Center for Biotechnology Information (NCBI) or The Institute Genomic Research (TIGR), were stored in tables accessible through the relational database management system MySQL on an Apache web server. To test for functionality of this database system, responses of S. mutans to environmental changes were analyzed using the database and 21 spots on the gel were identified as proteins whose expression had been increased or decreased by environmental pH change without in-gel trypsin digestion, protein extraction, or MALDI-TOF/TOF-MS (mass spectrometer) analysis. The identified proteins are agreement with those reported in previous papers on acid tolerance of S. mutans, demonstrating the usefulness of the system. This database is available at http://www.myamagu.dent.kyushu-u.ac.jp/~bioinformatics/index.html or http://www.bipos.mascat.nihon-u.ac.jp/index.html.

Acids↗

CASCAD: a database of annotated candidate single nucleotide polymorphisms associated with expressed sequences.

BACKGROUND: With the recent progress made in large-scale genome sequencing projects a vast amount of novel data is becoming available. A comparative sequence analysis, exploiting sequence information from various resources, can be used to uncover hidden information, such as genetic variation. Although there are enormous amounts of SNPs for a wide variety of organisms submitted to NCBI dbSNP and annotated in most genome assembly viewers like Ensembl and the UCSC Genome Browser, these platforms do not easily allow for extensive annotation and incorporation of experimental data supporting the polymorphism. However, such information is very important for selecting the most promising and useful candidate polymorphisms for use in experimental setups. DESCRIPTION: The CASCAD database is designed for presentation and query of candidate SNPs that are retrieved by in silico mining of high-throughput sequencing data. Currently, the database provides collections of laboratory rat (Rattus norvegicus) and zebrafish (Danio rerio) candidate SNPs. The database stores detailed information about raw data supporting the candidate, extensive annotation and links to external databases (e.g. GenBank, Ensembl, UniGene, and LocusLink), verification information, and predictions of a potential effect for non-synonymous polymorphisms in coding regions. The CASCAD website allows search based on an arbitrary combination of 27 different parameters related to characteristics like candidate SNP quality, genomic localization, and sequence data source or strain. In addition, the database can be queried with any custom nucleotide sequences of interest. The interface is crosslinked to other public databases and tightly coupled with primer design and local genome assembly interfaces in order to facilitate experimental verification of candidates. CONCLUSIONS: The CASCAD database discloses detailed information on rat and zebrafish candidate SNPs, including the raw data underlying its discovery. An advanced web-based search interface http://cascad.niob.knaw.nl allows universal access to the database content and allows various queries supporting many types of research utilizing single nucleotide polymorphisms.

Animals↗

Cataloging the relationships between proteins: a review of interaction databases.

By organizing and making widely accessible the increasing amounts of data from high-throughput analyses, protein interaction databases have become an integral resource for the biological community in relating sequence data with higher-order function. To provide a sense of the use and applicability of these databases, we describe each of the major comprehensive interaction databases as well as some of the more specialized ones. Content description, search/browse functionalities, and data presentation are discussed. A succinct explanation of database contents helps the user quickly identify whether the database contains applicable information to their research interest. Broad levels of search/browse functions as well as descriptions/examples allow users to quickly find and access pertinent data. At this point, clear presentation of search results as well as the primary content is necessary. Many databases display information graphically or divided into smaller digestible parts over a number of tabbed/linked pages. In addition, cross-linking between the databases promotes interconnectivity of the data and is an added layer of relational data for the user. Overall, although these protein interaction databases are under continual improvement, their current state shows that much time and effort has gone into organizing and presenting these large sets of data-describing protein interactions.

Database Management Systems↗