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At least 19 recordsLinked to original sources

PubMed2005

DoD: Database of Databases--updated molecular biology databases.

Database of Databases (DoD) is a collection of molecular biology databases extracted from Nucleic Acids Research, 2005 Database issue. DoD is constructed using javascript and html code. The 14 categories of 719 databases are provided with a search option, keyword help and database description linked to respective pages. Keyword help lists the search strings used to perform an individual search against categorized databases. Database description provides brief information about the database with a link to full-text article and main web page. DoD is available online and can be accessed at http://www.progenebio.in/DoD/DoD.htm.

Computational Biology↗

PubMed2003

Implications of the problem orientated medical record (POMR) for research using electronic GP databases: a comparison of the Doctors Independent Network Database (DIN) and the General Practice Research Database (GPRD).

BACKGROUND: The General Practice Research Database (GPRD) and Doctor's Independent Network Database (DIN), are large electronic primary care databases compiled in the UK during the 1990s. They provide a valuable resource for epidemiological and health services research. GPRD (based on VAMP) presents notes as a series of discrete episodes, whereas DIN is based on a system (MEDITEL) that used a Problem Orientated Medical Record (POMR) which links prescriptions to diagnostic problems. We have examined the implications for research of these different underlying philosophies. METHODS: Records of 40,183 children from 141 practices in DIN and 76,310 from 464 practices in GRPD who were followed to age 5 were used to compare the volume of recording of prescribing and diagnostic codes in the two databases. To assess the importance and additional value of the POMR within DIN, the appropriateness of diagnostic linking to skin emollient prescriptions was investigated. RESULTS: Variation between practices for both the number of days on which prescriptions were issued and diagnoses were recorded was marked in both databases. Mean number of "prescription days" during the first 5 years of life was similar in DIN (19.5) and in GPRD (19.8), but the average number of "diagnostic days" was lower in DIN (15.8) than in GPRD (22.9). Adjustment for linkage increased the average "diagnostic days" to 23.1 in DIN. 32.7% of emollient prescriptions in GPRD appeared with an eczema diagnosis on the same day compared to only 19.4% in DIN; however, 86.4% of prescriptions in DIN were linked to an earlier eczema diagnosis. More specifically 83% of emollient prescriptions appeared under a problem heading of eczema in the 121 practices that were using problem headings satisfactorily. CONCLUSION: Prescribing records in DIN and GPRD are very similar, but the usage of diagnostic codes is more parsimonious in DIN because of its POMR structure. Period prevalence rates will be underestimated in DIN unless this structure is taken into account. The advantage of the POMR is that in 121 of 141 practices using problem headings as intended, most prescriptions can be linked to a problem heading providing a specific reason for their issue.

Child, Preschool↗

PubMed2006

What is operative mortality? Defining death in a surgical registry database: a report of the STS Congenital Database Taskforce and the Joint EACTS-STS Congenital Database Committee.

The most concrete and universal outcome measure used in databases, whether governmental, professional society, research, or third-party payer, is operative mortality. To assure congruous data entry by multiple users of The Society of Thoracic Surgeons and the European Association for Cardiothoracic Surgery congenital heart surgery databases, operative mortality must be clearly defined. Traditionally, operative mortality has been defined as any death, regardless of cause, occurring (1) within 30 days after surgery in or out of the hospital, and (2) after 30 days during the same hospitalization subsequent to the operation. Differing hospital practices result in problems in use of the latter part of the definition (eg, the pediatric hospital that provides longer-term care will have higher mortality rates than one which transfers patients to another institution for such care). In addition, because of the significant number of pediatric multiple operation hospitalizations, issues of assignment of mortality to a specific operation within the hospitalization, calculation of operative mortality rates (operation based vs patient admission based), and discharge other than to home must be addressed and defined. We propose refinements to the definition of operative mortality which specifically meet the needs of our professional societies' multi-institutional registry databases, and at the same time are relevant and appropriate with respect to the goals and purposes of administrative databases, government agencies, and the general public.

Cardiac Surgical Procedures↗

PubMedDate not supplied

Comparison of the NCI open database with seven large chemical structural databases.

Eight large chemical databases have been analyzed and compared to each other. Central to this comparison is the open National Cancer Institute (NCI) database, consisting of approximately 250 000 structures. The other databases analyzed are the Available Chemicals Directory ("ACD," from MDL, release 1.99, 3D-version); the ChemACX ("ACX," from CamSoft, Version 4.5); the Maybridge Catalog and the Asinex database (both as distributed by CamSoft as part of ChemInfo 4.5); the Sigma-Aldrich Catalog (CD-ROM, 1999 Version); the World Drug Index ("WDI," Derwent, version 1999.03); and the organic part of the Cambridge Crystallographic Database ("CSD," from Cambridge Crystallographic Data Center, 1999 Version 5.18). The database properties analyzed are internal duplication rates; compounds unique to each database; cumulative occurrence of compounds in an increasing number of databases; overlap of identical compounds between two databases; similarity overlap; diversity; and others. The crystallographic database CSD and the WDI show somewhat less overlap with the other databases than those with each other. In particular the collections of commercial compounds and compilations of vendor catalogs have a substantial degree of overlap among each other. Still, no database is completely a subset of any other, and each appears to have its own niche and thus "raison d'être". The NCI database has by far the highest number of compounds that are unique to it. Approximately 200 000 of the NCI structures were not found in any of the other analyzed databases.

Cluster Analysis↗

PubMed1995

Enhancing the diversity of a corporate database using chemical database clustering and analysis.

The contribution that the Chemical Abstracts structural database (CAST-3D) and the Maybridge database (MAY) would make to diversifying the structural information and property space spanned by our corporate database (CBI) is assessed. A subset of the CAST-3D database has been selected to augment the structural diversity of various electronic databases used in computer-assisted drug design projects. The analysis of the MAY database directly offers the potential to expand the CBI compound library, but also provides a source for structural diversity in a format suitable for computer-assisted database searching and molecular design. The analysis performed is twofold. First, a nonhierarchical clustering technique available in the Daylight clustering package is applied to evaluate the structural differences between databases. The comparison is then extended to analyze various structure-derived property spaces calculated from molecular descriptors such as the logarithm of the octanol-water partition coefficient (CLOGP), the molar refractivity (CMR) and the electronic dipole moment (CDM). The diversity contribution of each database to these property spaces is quantified in relation to our corporate database.

Chemical Phenomena↗

PubMed2006

Validation of the Provincial Transfer Authorization Centre database: a comprehensive database containing records of all inter-facility patient transfers in the province of Ontario.

BACKGROUND: The Provincial Transfer Authorization Centre (PTAC) was established as a part of the emergency response in Ontario, Canada to the Severe Acute Respiratory Syndrome (SARS) outbreak in 2003. Prior to 2003, data relating to inter-facility patient transfers were not collected in a systematic manner. Then, in an emergency setting, a comprehensive database with a complex data collection process was established. For the first time in Ontario, population-based data for patient movement between healthcare facilities for a population of twelve million are available. The PTAC database stores all patient transfer data in a large database. There are few population-based patient transfer databases and the PTAC database is believed to be the largest example to house this novel dataset. A patient transfer database has also never been validated. This paper presents the validation of the PTAC database. METHODS: A random sample of 100 patient inter-facility transfer records was compared to the corresponding institutional patient records from the sending healthcare facilities. Measures of agreement, including sensitivity, were calculated for the 12 common data variables. RESULTS: Of the 100 randomly selected patient transfer records, 95 (95%) of the corresponding institutional patient records were located. Data variables in the categories patient demographics, facility identification and timing of transfer and reason and urgency of transfer had strong agreement levels. The 10 most commonly used data variables had accuracy rates that ranged from 85.3% to 100% and error rates ranging from 0 to 12.6%. These same variables had sensitivity values ranging from 0.87 to 1.0. CONCLUSION: The very high level of agreement between institutional patient records and the PTAC data for fields compared in this study supports the validity of the PTAC database. For the first time, a population-based patient transfer database has been established. Although it was created during an emergency situation and data collection is dependent on front-line medical workers, the PTAC data has achieved a high level of validity, perhaps even higher than many purpose built databases created during non-emergency settings.

Database Management Systems↗

PubMed2002

PFDB: a generic protein family database integrating the CATH domain structure database with sequence based protein family resources.

MOTIVATION: The PFDB (Protein Family Database) is a new database designed to integrate protein family-related data with relevant functional and genomic data. It currently manages biological data for three projects-the CATH protein domain database (Orengo et al., 1997; Pearl et al., 2001), the VIDA virus domains database (Albà et al., 2001) and the Gene3D database (Buchan et al., 2001). The PFDB has been designed to accommodate protein families identified by a variety of sequence based or structure based protocols and provides a generic resource for biological research by enabling mapping between different protein families and diverse biochemical and genetic data, including complete genomes. RESULTS: A characteristic feature of the PFDB is that it has a number of meta-level entities (for example aggregation, collection and inclusion) represented as base tables in the final design. The explicit representation of relationships at the meta-level has a number of advantages, including flexibility-both in terms of the range of queries that can be formulated and the ability to integrate new biological entities within the existing design. A potential drawback with this approach-poor performance caused by the number of joins across meta-level tables-is avoided by implementing the PFDB with materialized views using the mature relational database technology of Oracle 8i. The resultant database is both fast and flexible. This paper presents the principles on which the database has been designed and implemented, and describes the current status of the database and query facilities supported.

Database Management Systems↗

PubMed1995

Toxicology databases in the metadatabank of online databases.

Databases in science and technology dealing with toxicology subjects are of great and increasing interest to the scientific community. International hosts pay their tribute in creating toxicology clusters as a user-aid. Toxicology clusters of DataStar, DIALOG, DIMDI and STN are listed and compared. At the German National Research Centre for Environment and Health an 'Information System for Environmental Chemicals' has been developed. Within this research project approximately 400 online databases have been evaluated and the results are stored in the Metadatabank of Online Databases called DADB. A further step in this project is to assist the users of these metadatabases to choose the most appropriate database(s) for a special query. The retrieval of information out of a multitude of differently structured databases can be optimized using different evaluation criteria. We distinguished three groups of evaluation criteria: (1) general evaluation criteria, e.g. size of database, update frequency, cost of online search, etc., (2) evaluation criteria based on the characterization of environmental chemicals, and (3) evaluation criteria based on environmental-relevant data-types. We studied the influence of a number of different criteria in order to rank a set of objects, in this particular case toxicology databases. We used a six-number scoring system. The scoring is carried out using the scientific background of lattice theory and its graphical evaluation. The application of this scoring system for toxicologically-relevant databases, which is still in an early development stage, is useful in selecting the most appropriate database(s) in accordance with special items of interest. Applying our five chosen criteria, the databank CA (Chemical Abstracts) turns out to be the best, followed by four other databanks, which cannot be compared with each other.

Databases, Factual↗

PubMed1998

NHLBI workshop on the utilization of ECG databases: preservation and use of existing ECG databases and development of future resources.

Baseline examinations and periodic reexaminations in longitudinal population studies, together with ongoing surveillance for morbidity and mortality, provide unique opportunities for seeking ways to enhance the value of the electrocardiogram (ECG) recorded with digital technology as an inexpensive and noninvasive tool for prognosis and diagnosis. Clinicians, epidemiologists, and engineers from industry, government, and academic medical centers gathered at a workshop sponsored by the National Heart, Lung, and Blood Institute (NHLBI) on June 11-12, 1997, to discuss the research potential of ECG databases, their preservation and accession, and standards for recording and storage. Databases considered were those acquired in ongoing and future NHLBI-funded studies and in clinical settings in which the ECG continues to provide valuable information for evaluation and treatment. The accessibility of existing databases, the quality of their data, and the availability of ancillary demographic and clinical information were major themes. Also discussed were appropriate statistical methodologies to be used with these data for developing and testing ECG algorithms. The workshop participants affirmed the value of these databases and urged the establishment of an ECG advisory and review group to (1) resolve technical and proprietary issues for the utilization of currently existing databases; (2) develop standards for recording, storage, and utilization of ECGs in future NHLBI-supported studies; (3) oversee the creation of a national ECG database resource, consisting of an archive of ECG databases from past and ongoing NHLBI-supported studies, and a registry of ECG databases that would eventually include digital ECGs from populations currently underrepresented in the demographic spectrum of the NHLBI databases.

Adolescent↗

PubMed1999

Searching the right database. A comparison of four databases for psychiatry journals.

Journal coverage is one factor that affects the retrieval of relevant information from bibliographic databases. The aims of this study were to investigate the coverage of databases for psychiatry journals, and to assess the overlap between databases. Psychiatry journals were identified using Ulrich's International Periodicals Directory and then analysed to see which bibliographic databases indexed the most journals. A total of 213 abstracting and indexing services were listed as indexing at least one of the 977 psychiatry journals identified. The four most frequently cited databases (PSYCLIT, EMBASE, BIOSIS and MEDLINE) indexed 506 (52%) of the psychiatry journals. Of these 506 journals, PSYCLIT indexed 367 (73%), EMBASE 337 (67%), BIOSIS 243 (48%) and MEDLINE 236 (47%). Combining the databases with the highest yields (PSYCLIT and EMBASE) increased the number of journals indexed to 461 (91%). The four databases combined accounted for 90% of all psychiatry journals found to be indexed by at least one abstracting and indexing service. More than 400 journals were not indexed at all. Variations in the overlap between PSYCLIT, EMBASE, BIOSIS and MEDLINE, and the high proportion (35%) of journals indexed in only one of these four databases emphasize the importance of searching more than one or even two databases to ensure optimal coverage of the literature.

Abstracting and Indexing↗

PubMedDate not supplied

A checklist for retrospective database studies--report of the ISPOR Task Force on Retrospective Databases.

INTRODUCTION: Health-related retrospective databases, in particular claims databases, continue to be an important data source for outcomes research. However, retrospective databases pose a series of methodological challenges, some of which are unique to this data source. METHODS: In an effort to assist decision makers in evaluating the quality of published studies that use health-related retrospective databases, a checklist was developed that focuses on issues that are unique to database studies or are particularly problematic in database research. This checklist was developed primarily for the commonly used medical claims or encounter-based databases but could potentially be used to assess retrospective studies that employ other types of databases, such as disease registries and national survey data. RESULTS: Written in the form of 27 questions, the checklist can be used to guide decision makers as they consider the database, the study methodology, and the study conclusions. Checklist questions cover a wide range of issues, including relevance, reliability and validity, data linkages, eligibility determination, research design, treatment effects, sample selection, censoring, variable definitions, resource valuation, statistical analysis, generalizability, and data interpretation. CONCLUSIONS: For many of the questions, key references are provided as a resource for those who want to further examine a particular issue.

Data Interpretation, Statistical↗

PubMed2002

Practical experience with databases for congenital heart disease: a registry versus an academic database.

Increasingly, pooled data from multiple institutions are the source of published clinical results. A computerized database program is essential to compile and analyze clinical experience. The scope of data collection defines a database. Two types of databases, the registry and academic, are compared. In a registry database, some of the data are collected on all patients. The resources dedicated to data collection and entry are the practical limit to the extent of information in the database. The agreement on nomenclature for surgical diagnosis and procedure codes of congenital heart disease has paved the way for the development of a multi-institutional registry database. The registry database could provide a standard of care reference for early results after congenital heart surgery. The practical difficulty of data collection is obviated by limiting information to a basic minimum dataset. The academic database, in which all of the data are collected for a defined subset of patients, is designed to investigate a specific population of patients to generate new knowledge. It contains sufficient data to allow sophisticated statistical analysis to clarify the determinants of good and poor outcome, including early, mid- and long-term follow-up information. Multi-institutional pooling of detailed information derived from academic databases will be of increasing importance in generating new knowledge to foster improved therapy for patients with congenital heart disease.

Cardiac Surgical Procedures↗

PubMed2005

A technical infrastructure to conduct randomized database studies facilitated by a general practice research database.

General practice research databases are increasingly used to study intended and unintended effects of treatments. However, confounding by indication remains a major problem. The randomized database study methodology has been proposed as a method to combine the strengths of observational database (generalizability) and the strength of the randomized clinical trial (RCT) design (randomization). We developed an infrastructure that enables the execution of randomized database studies with treatment randomization facilitated by a general practice research database. The requirements posed by the methodology of randomized database studies were facilitated by software components. Our assessment showed that it is technically possible to conduct randomized trials in general practice according to the randomized database design. The infrastructure facilitated the conduct of randomized database studies in general practice but some practical difficulties and methodological issues remain. The technical infrastructure seems to be both promising and potentially feasible to facilitate future randomized database studies, although the methodology needs to be evaluated in more detail.

Biomedical Research↗

PubMedDate not supplied

Molecular diversity in chemical databases: comparison of medicinal chemistry knowledge bases and databases of commercially available compounds.

A molecular descriptor space has been developed which describes structural diversity. Large databases of molecules have been mapped into it and compared. This analysis used five chemical databases, CMC and MDDR, which represent knowledge bases containing active medicinal agents, ACD and SPECS, two databases of commercially available compounds, and finally the Wellcome Registry. Together these databases contained more than 300,000 structures. Topological indices and the free energy of solvation were computed for each compound in the databases. Factor analysis was used to reduce the dimensionality of the descriptor space. Low density observations were deleted as a way of removing outliers, which allowed a further reduction in the descriptor space of interest. The five databases could then be compared on an efficient basis using a metric developed for this purpose. A Riemann gridding scheme was used to subdivide the factor space into subhypercubes to obtain accurate comparisons. Most of the 300,000 structures were highly clustered, but unique structures were found. An analysis of overlap between the biological and commercial databases was carried out. The metric provides a useful algorithm for choosing screening sets of diverse compounds from large databases.

Artificial Intelligence↗

PubMed2004

Kidney gene database: a curated and integrated database of genes involved in kidney disease.

PURPOSE: We have created a curated and integrated database, the Kidney Gene Database (KGDB) (http://www.urogene.org/kgdb) that contains current information about genes or genomic loci involved in human kidney disease. MATERIALS AND METHODS: Genes that undergo molecular, genetic or epigenetic events that affect kidney function are identified through a biomedical literature search and catalogued in the database. RESULTS: Events that are currently screened for are gene amplification, mutation, deletion, polymorphism, loss of heterozygosity, DNA methylation and DNA hypomethylation. In addition, genes that are uniquely expressed in the kidney, as determined by analyzing the expressed sequence tags database and the Serial Analysis of Gene Expression database, are also included in KGDB. For each gene KGDB provides basic information about the gene product, a tissue type gene expression profile, links to protein, mRNA and genomic DNA sequence information, relevant literature citations and cross-references to other databases. CONCLUSIONS: We present KGDB, which is to our knowledge the first curated and integrated database of genes involved in human kidney disease. KGDB is free, widely accessible and easy to use, and it provides a wealth of relevant information. In addition, KGDB will be continuously updated every 6 months to include new information published in the biomedical literature or in gene expression databases. We envision that KGDB will serve as a valuable resource for scientists and clinicians.

Databases, Genetic↗

PubMed2004

Utility and limitations of genetic disease databases in clinical genetics research: a neurofibromatosis 1 database example.

Databases that collect clinical information on patients with particular genetic diseases can be used to investigate the clinical history of a disorder, its genetics, and genotype-phenotype correlations. A database can also serve as a valuable source of patients for studies of disease pathogenesis, variability, or treatment. We review the strengths and limitations of genetic disease databases in the context of our experience with the National Neurofibromatosis Foundation International Database (NNFFID). Genetic disease databases have been developed by individual investigators, scientific consortia, patient support organizations, and commercial enterprises. Databases vary from simple lists of affected individuals to comprehensive collections of detailed clinical and genetic information. Data may be obtained from people who volunteer to be included, systematic assessments of patients seen at participating medical centers, or population-based registries. Access to information may be highly restricted or widely available. These variables all affect the possible uses and usefulness of the data for research. Technical aspects of data entry, organization, storage, and retrieval, as well as issues related to data quality, confidentiality, and security, help determine how well a system actually functions. We discuss examples of research that have been accomplished with genetic disease databases and make recommendations regarding the organization and operation of these resources.

Biomedical Research↗

PubMed2005

The interactive online SKY/M-FISH & CGH database and the Entrez cancer chromosomes search database: linkage of chromosomal aberrations with the genome sequence.

To catalog data on chromosomal aberrations in cancer derived from emerging molecular cytogenetic techniques and to integrate these data with genome maps, we have established two resources, the NCI and NCBI SKY/M-FISH & CGH Database and the Cancer Chromosomes database. The goal of the former is to allow investigators to submit and analyze clinical and research cytogenetic data. It contains a karyotype parser tool, which automatically converts the ISCN short-form karyotype into an internal representation displayed in detailed form and as a colored ideogram with band overlay, and also has a tool to compare CGH profiles from multiple cases. The Cancer Chromosomes database integrates the SKY/M-FISH & CGH Database with the Mitelman Database of Chromosome Aberrations in Cancer and the Recurrent Chromosome Aberrations in Cancer database. These three datasets can now be searched seamlessly by use of the Entrez search and retrieval system for chromosome aberrations, clinical data, and reference citations. Common diagnoses, anatomic sites, chromosome breakpoints, junctions, numerical and structural abnormalities, and bands gained and lost among selected cases can be compared by use of the "similarity" report. Because the model used for CGH data is a subset of the karyotype data, it is now possible to examine the similarities between CGH results and karyotypes directly. All chromosomal bands are directly linked to the Entrez Map Viewer database, providing integration of cytogenetic data with the sequence assembly. These resources, developed as a part of the Cancer Chromosome Aberration Project (CCAP) initiative, aid the search for new cancer-associated genes and foster insights into the causes and consequences of genetic alterations in cancer.

Base Sequence↗

PubMed2002

Arab genetic disease database (AGDDB): a population-specific clinical and mutation database.

Here we present the Arab Genetic Disease Database (AGDDB), a curated catalog of genetic disorders found in Arab populations. The first release of the database is populated primarily with information from the textbook Genetic Disorders Among Arab Populations [Teebi and Farag, 1997]. AGDDB is composed of data elements revolving around disorder reports. Other reports cover clinical, genomic, reference, and population frequency elements and their important attributes. The Arab Genetic Disease Consortium (30 investigators, 18 countries) is responsible for editing and reviewing AGDDB data. After initial indexing, AGDDB contains over 1,000 unique disorder entries. Entries are linked to their counterparts in the Online Mendelian Inheritance in Man (OMIM) database; similar associations with relevant locus-specific and central mutation databases are planned. The database can be queried by keyword across all its fields, with more focused searches allowed. The database is freely available and may be accessed at www.agddb.org. The database serves as a robust prototype for cataloging variation and disorder information within a specific population.

Arabs↗