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PubMed2005

ArrayExpress--a public repository for microarray gene expression data at the EBI.

ArrayExpress is a public repository for microarray data that supports the MIAME (Minimum Information About a Microarray Experiment) requirements and stores well-annotated raw and normalized data. As of November 2004, ArrayExpress contains data from approximately 12,000 hybridizations covering 35 species. Data can be submitted online or directly from local databases or LIMS in a standard format, and password-protected access to prepublication data is provided for reviewers and authors. The data can be retrieved by accession number or queried by various parameters such as species, author and array platform. A facility to query experiments by gene and sample properties is provided for a growing subset of curated data that is loaded in to the ArrayExpress data warehouse. Data can be visualized and analysed using Expression Profiler, the integrated data analysis tool. ArrayExpress is available at http://www.ebi.ac.uk/arrayexpress.

Animals↗
PubMed2005

TmaDB: a repository for tissue microarray data.

BACKGROUND: Tissue microarray (TMA) technology has been developed to facilitate large, genome-scale molecular pathology studies. This technique provides a high-throughput method for analyzing a large cohort of clinical specimens in a single experiment thereby permitting the parallel analysis of molecular alterations (at the DNA, RNA, or protein level) in thousands of tissue specimens. As a vast quantity of data can be generated in a single TMA experiment a systematic approach is required for the storage and analysis of such data. DESCRIPTION: To analyse TMA output a relational database (known as TmaDB) has been developed to collate all aspects of information relating to TMAs. These data include the TMA construction protocol, experimental protocol and results from the various immunocytological and histochemical staining experiments including the scanned images for each of the TMA cores. Furthermore the database contains pathological information associated with each of the specimens on the TMA slide, the location of the various TMAs and the individual specimen blocks (from which cores were taken) in the laboratory and their current status i.e. if they can be sectioned into further slides or if they are exhausted. TmaDB has been designed to incorporate and extend many of the published common data elements and the XML format for TMA experiments and is therefore compatible with the TMA data exchange specifications developed by the Association for Pathology Informatics community. Finally the design of the database is made flexible such that TMA experiments from several types of cancer can be stored in a single database, which incorporates the national minimum data set required for pathology reports supported by the Royal College of Pathologists (UK). CONCLUSION: TmaDB will provide a comprehensive repository for TMA data such that a large number of results from the numerous immunostaining experiments can be efficiently compared for each of the TMA cores. This will allow a systematic, large-scale comparison of tumour samples to facilitate the identification of gene products of clinical importance such as therapeutic or prognostic markers. In addition this work will contribute to the establishment of a standard for reporting TMA data analogous to MIAME in the description of microarray data.

Data Interpretation, Statistical↗
PubMedDate not supplied

Generic data modeling for clinical repositories.

OBJECTIVE: To construct a large-scale clinical repository that accurately captures a detailed understanding of the data vital to the process of health care and that provides highly efficient access to patient information for the users of a clinical information system. DESIGN: Conventional approaches to data modeling encourage the development of a highly specific data schema in order to capture as much information as possible about a given domain. In contrast, current database technology functions most effectively for clinical databases when a generic data schema is used. The technique of "generic data modeling" is presented as a method of reconciling these opposing views of clinical data, using formal operations to transform a detailed schema into a generic one. RESULTS: A complex schema consisting of hundreds of entities and representing a rich set of constraints about the patient care domain is transformed into a generic schema consisting of roughly two dozen tables. The resulting database design is efficient for patient-oriented queries and is highly flexible in adapting to the changing information needs of a health care institution, particularly changes involving the collection of new data elements. CONCLUSION: Conventional approaches to data modeling can be used to develop rich, complex models of clinical data that are useful for understanding and managing the process of patient care. Generic data modeling techniques can successfully transform a detailed design into an efficient generic design that is flexible enough to meet the needs of an operational clinical information system.

Hospital Information Systems↗
PubMed2007

Proteomic data exchange and storage: the need for common standards and public repositories.

The ever increasing volumes of proteomic data now being produced by laboratories across the world have resulted in major issues in data storage and accessibility. The further demands of multilaboratory initiatives has highlighted issues when collaborators cannot import data generated within the same project but generated by different hardware types and processed by laboratory-specific work flows and analyses packages. There is an increasing need for common data standards that will allow the interchange of data between different instrumentation, search engines, and between laboratory databases. This could then lead to the establishment of data repositories from where benchmark datasets could be accessed and reanalyzed. The Human Proteome Organization is currently supporting efforts to establish such standards. The work of the Proteomics Standards Initiative has lead to the development of the mzData XML interchange standard and is now broadening its scope to produce a spectral analysis output format, mzIdent. Accompanying controlled vocabularies allow the accurate, while systematic, representation of metadata throughout both schema.

Benchmarking↗
PubMed2026

Computational metabolomics at scale: from open data to insight.

Metabolomics data are currently generated at scale thanks to the evolution of technologies that have led to marked improvements in the number of metabolites detected, spanning all chemical classes. These data are increasingly submitted to public repositories for data reuse, integration, and interpretation. Despite the availability of public resources and associated computational tools, the field still lacks a widely adopted, consistent data and analytics infrastructure capable of transforming this wealth of information into scientific insight. Indeed, the metabolomics field is just now scratching the surface of being able to harness the power of new computational technologies. In this review, we summarize discussions from the "Dagstuhl-Seminar 24181 Computational Metabolomics: Towards Molecules, Models, and their Meaning" with a focus on public data availability, open data standards, data and knowledge integration, and education. Our goal is to raise awareness and adoption of the latest open science resources while highlighting key areas needing further development.

Metabolomics↗
PubMed2004

The Electronic Report on Adolescent Pregnancy (ERAP).

PURPOSE: To create a data management system that: (1) standardizes antecedent, program, and outcome variables relevant to the shared goals of adolescent-oriented maternity programs while allowing users to add variables pertaining to unique aspects of their work; (2) cues providers to physiologic and psychosocial characteristics that predispose teenagers to adverse pregnancy and parenting outcomes, (3) standardizes patient care by guiding providers through adolescent-oriented prenatal, postpartum, and well baby visits, and (4) establishes the infrastructure to collect data from a nationally representative sample of pregnant and parenting teens. METHOD: We adapted a powerful, state-of-the-art relational database framework (Microsoft Access 2000) to create an easy-to-use data management system-The Electronic Report on Adolescent Pregnancy (ERAP)-that requires minimal training to use on a personal computer. RESULTS: ERAP is designed to meet the administrative and analytic needs of adolescent-oriented maternity programs. It consists of six linked core data tables (teen, pregnancy, prenatal visits, child, interconception interval, and interconception interval visits), that allow users to analyze data from these multiple views while preserving the family structure. In addition, the database standardizes methods for collecting and storing the information and automatically computing the variables needed to monitor and evaluate an adolescent-oriented maternity program. Since by adding variables and appending supplementary tables, users can modify the core database to accommodate unique aspects of their programs and/or research, ERAP is also an ideal conduit for translating research findings into clinical practice. Similarly, because ERAP actually structures the care patients receive, the database provides the infrastructure needed to develop and implement best practice guidelines for treating teen-headed families. Finally, the confidentiality of all subject data is assured because ERAP is password-protected and automatically prepares files for batched external analyses by removing personal identifiers. CONCLUSIONS: ERAP provides the infrastructure needed to create a teen-pregnancy databank at the national level and an efficient patient monitoring system at the program level. By standardizing variable definitions and data collection techniques, serving as a repository for data collected at multiple sites, and tracking the multidisciplinary aspects of the care patients receive, ERAP has the potential to facilitate collaboration between adolescent-oriented maternity programs, increase the scientific rigor of teen pregnancy research, and improve the quality of care individual teen-headed families receive by prompting compliance with best practice guidelines.

Adolescent↗
PubMed2001

Progenetix.net: an online repository for molecular cytogenetic aberration data.

UNLABELLED: Through sequencing projects and, more recently, array-based expression analysis experiments, a wealth of genetic data has become accessible via online resources. In contrast, few of the (molecular-) cytogenetic aberration data collected in the last decades are available in a format suitable for data mining procedures. www.progenetix.net is a new online repository for previously published chromosomal aberration data, allowing the addition of band-specific information about chromosomal imbalances to oncologic data analysis efforts. AVAILABILITY: http://www.progenetix.net CONTACT: mbaudis@stanford.edu

Chromosome Aberrations↗
PubMed1991

Implications of the National Practitioner Data Bank for nurse practitioners.

The National Practitioner Data Bank is a new federal repository of data on malpractice payments and adverse actions taken against the clinical privileges and licenses of all health care practitioners. This article summarizes the law governing the data bank and its implications for nurse practitioners. Specific reporting requirements are discussed, as well as guidelines for those who must and those who can access the data bank. This article also explains how NPs are notified when reports are made and gives methods for correcting errors in reports.

Data Collection↗
PubMed1996

A Web-based repository manager for brain mapping data.

The Web provides a rapid prototyping environment for building platform-independent graphical user interfaces. A Web-based console can be implemented as a suite of CGI scripts that generate HTML code, manipulate files, execute system commands, and invoke external tools. Often these tools share data by reading and writing flat files, which must be explicitly maintained by the CGI programmer. In a repository system, meta-data about each file object are maintained in a database, and access to all data is regulated by a layer of control services. This paper describes the design and implementation of a Web-based Repository Manager (WRM), which provides an application programmer's interface for controlling applications, generating HTML documents, handling Web forms, and managing multi-media data. The WRM is being used to develop a console for the Brain Mapping Framework, a system for visualizing cortical stimulation data obtained during neurosurgery.

Brain Mapping↗
PubMed2003

caCORE: a common infrastructure for cancer informatics.

MOTIVATION: Sites with substantive bioinformatics operations are challenged to build data processing and delivery infrastructure that provides reliable access and enables data integration. Locally generated data must be processed and stored such that relationships to external data sources can be presented. Consistency and comparability across data sets requires annotation with controlled vocabularies and, further, metadata standards for data representation. Programmatic access to the processed data should be supported to ensure the maximum possible value is extracted. Confronted with these challenges at the National Cancer Institute Center for Bioinformatics, we decided to develop a robust infrastructure for data management and integration that supports advanced biomedical applications. RESULTS: We have developed an interconnected set of software and services called caCORE. Enterprise Vocabulary Services (EVS) provide controlled vocabulary, dictionary and thesaurus services. The Cancer Data Standards Repository (caDSR) provides a metadata registry for common data elements. Cancer Bioinformatics Infrastructure Objects (caBIO) implements an object-oriented model of the biomedical domain and provides Java, Simple Object Access Protocol and HTTP-XML application programming interfaces. caCORE has been used to develop scientific applications that bring together data from distinct genomic and clinical science sources. AVAILABILITY: caCORE downloads and web interfaces can be accessed from links on the caCORE web site (http://ncicb.nci.nih.gov/core). caBIO software is distributed under an open source license that permits unrestricted academic and commercial use. Vocabulary and metadata content in the EVS and caDSR, respectively, is similarly unrestricted, and is available through web applications and FTP downloads. SUPPLEMENTARY INFORMATION: http://ncicb.nci.nih.gov/core/publications contains links to the caBIO 1.0 class diagram and the caCORE 1.0 Technical Guide, which provide detailed information on the present caCORE architecture, data sources and APIs. Updated information appears on a regular basis on the caCORE web site (http://ncicb.nci.nih.gov/core).

Animals↗
PubMed1995

Extending a clinical repository to include multiple sites.

With the consolidation of health care organizations and services, a clinical repository comprising data from a single site is no longer sufficient. Individual patient data are now spread across multiple sites comprising a single enterprise. Users require an integrated view, or at least a common view, of these clinical data across multiple sites. Many issues arise when one tries to merge data from multiple, distinct organizations into an existing schema. We have addressed these issues while extending our clinical repository for Barnes Hospital with data from Jewish Hospital, both of which are members of the recently formed BJC Health System. We describe the architecture of our existing repository, approaches and issues in extending this repository to include multiple sites, and the specific issues we addressed in our system.

Computer Communication Networks↗
PubMed2005

YeastHub: a semantic web use case for integrating data in the life sciences domain.

MOTIVATION: As the semantic web technology is maturing and the need for life sciences data integration over the web is growing, it is important to explore how data integration needs can be addressed by the semantic web. The main problem that we face in data integration is a lack of widely-accepted standards for expressing the syntax and semantics of the data. We address this problem by exploring the use of semantic web technologies-including resource description framework (RDF), RDF site summary (RSS), relational-database-to-RDF mapping (D2RQ) and native RDF data repository-to represent, store and query both metadata and data across life sciences datasets. RESULTS: As many biological datasets are presently available in tabular format, we introduce an RDF structure into which they can be converted. Also, we develop a prototype web-based application called YeastHub that demonstrates how a life sciences data warehouse can be built using a native RDF data store (Sesame). This data warehouse allows integration of different types of yeast genome data provided by different resources in different formats including the tabular and RDF formats. Once the data are loaded into the data warehouse, RDF-based queries can be formulated to retrieve and query the data in an integrated fashion. AVAILABILITY: The YeastHub website is accessible via the following URL: http://yeasthub.gersteinlab.org.

Biology↗
PubMed2006

[caCORE: core architecture of bioinformation on cancer research in America].

A critical factor in the advancement of biomedical research is the ease with which data can be integrated, redistributed and analyzed both within and across domains. This paper summarizes the Biomedical Information Core Infrastructure built by National Cancer Institute Center for Bioinformatics in America (NCICB). The main product from the Core Infrastructure is caCORE--cancer Common Ontologic Reference Environment, which is the infrastructure backbone supporting data management and application development at NCICB. The paper explains the structure and function of caCORE: (1) Enterprise Vocabulary Services (EVS). They provide controlled vocabulary, dictionary and thesaurus services, and EVS produces the NCI Thesaurus and the NCI Metathesaurus; (2) The Cancer Data Standards Repository (caDSR). It provides a metadata registry for common data elements. (3) Cancer Bioinformatics Infrastructure Objects (caBIO). They provide Java, Simple Object Access Protocol and HTTP-XML application programming interfaces. The vision for caCORE is to provide a common data management framework that will support the consistency, clarity, and comparability of biomedical research data and information. In addition to providing facilities for data management and redistribution, caCORE helps solve problems of data integration. All NCICB-developed caCORE components are distributed under open-source licenses that support unrestricted usage by both non-profit and commercial entities, and caCORE has laid the foundation for a number of scientific and clinical applications. Based on it, the paper expounds caCORE-base applications simply in several NCI projects, of which one is CMAP (Cancer Molecular Analysis Project), and the other is caBIG (Cancer Biomedical Informatics Grid). In the end, the paper also gives good prospects of caCORE, and while caCORE was born out of the needs of the cancer research community, it is intended to serve as a general resource. Cancer research has historically contributed to many areas beyond tumor biology. At the same time, the paper makes some suggestions about the study at the present time on biomedical informatics in China.

Computational Biology↗
PubMed1991

A variant database.

Variant biomacromolecules, either natural or artificially created, are proving to be useful in determining structure-function relationships. Research in this field would be facilitated by the compilation of data of variants into a central and widely available repository. The Variant Database acts as a repository for data concerning variant molecules. It complements the Biological Activity and the Physicochemical Property Databases as well as provides variant sequences.

Amino Acid Sequence↗
PubMed2026

SeqUIaSCOPE: multi-omics data integration platform for single-patient clinical oncology pathway exploration.

SUMMARY: SeqUIaSCOPE is an open-source platform designed for routine clinical oncology diagnostics through case-centric integration and visualization of genomic variants, fusion events, and expression profiles. The platform combines molecular-level validation via embedded genome browsing with systems-level interpretation through dynamic pathway visualization, enabling geneticists to assess how alterations converge across biological networks. Flexible reporting with customizable templates accommodates diverse institutional requirements, while secure cluster-based or local deployment ensures compliance with data protection policies, making advanced multi-omics diagnostics accessible to academic and clinical institutions. AVAILABILITY AND IMPLEMENTATION: SeqUIaSCOPE is freely available on GitHub at https://github.com/BioIT-CEITEC/sequiascope under the MIT license and archived at Zenodo (https://zenodo.org/records/21338445). Due to the sensitive nature of patient data, the repository provides simulated datasets that mimic the structure of real clinical data for testing and exploration. Documentation and a live demo accompany these datasets, allowing users to explore the application without any prior setup. The repository also includes a Helm chart for Kubernetes deployment and Docker containers for local deployment, ensuring compatibility across Linux, macOS, and Windows. No user registration is required, and all data remains on local or institutional infrastructure.

Humans↗