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At least 397 records · Page 22Linked to original sources
PubMed2004

Bioinformatics integration and agent technology.

Vast amounts of life sciences data are scattered around the world in the form of a variety of heterogeneous data sources. The need to be able to co-relate relevant information is fundamental to increase the overall knowledge and understanding of a specific subject. Bioinformaticians aspire to find ways to integrate biological data sources for this purpose and system integration is a very important research topic. The purpose of this paper is to provide an overview of important integration issues that should be considered when designing a bioinformatics integration system. The currently prevailing approach for integration is presented with examples of bioinformatics information systems together with their main characteristics. Here, we introduce agent technology and we argue why it provides an appropriate solution for designing bioinformatics integration systems.

Algorithms↗
PubMed1997

An intranet database for pacemaker patients.

A database system, incorporating smartcard technologies, was designed to hold the personal and pacing details of pacemaker patients, who attended a clinic at the Royal Sussex County Hospital (RSCH), Brighton, UK. Following an initial period of a 12 month clinical trial, with the database running on a standalone personal computer, the Pacemaker Patient Database has been redesigned and implemented as an intranet-based system. This paper describes the issues relating to the development of the new prototype system and identifies the design principles for intranet-based electronic health care (EHCR) record database systems.

Computer Communication Networks↗
PubMed2000

ProClass protein family database.

ProClass is a protein family database that organizes non-redundant sequence entries into families defined collectively by PIR superfamilies and PROSITE patterns. By combining global similarities and functional motifs into a single classification scheme, ProClass helps to reveal domain and family relationships and classify multi-domain proteins. The database currently consists of >155 000 sequence entries retrieved from both PIR-International and SWISS-PROT databases. Approximately 92 000 or 60% of the ProClass entries are classified into approximately 6000 families, including a large number of new members detected by our GeneFIND family identification system. The ProClass motif collection contains approximately 72 000 motif sequences and >1300 multiple alignments for all PROSITE patterns, including >21 000 matches not listed in PROSITE and mostly detected from unique PIR sequences. To maximize family information retrieval, the database provides links to various protein family, domain, alignment and structural class databases. With its high classification rate and comprehensive family relationships, ProClass can be used to support full-scale genomic annotation. The database, now being implemented in an object-relational database management system, is available for online sequence search and record retrieval from our WWW server at http://pir.georgetown.edu/gfserver/proclass.html

Databases, Factual↗
PubMed2005

HBVPathDB: a database of HBV infection-related molecular interaction network.

AIM: To describe molecules or genes interaction between hepatitis B viruses (HBV) and host, for understanding how virus' and host's genes and molecules are networked to form a biological system and for perceiving mechanism of HBV infection. METHODS: The knowledge of HBV infection-related reactions was organized into various kinds of pathways with carefully drawn graphs in HBVPathDB. Pathway information is stored with relational database management system (DBMS), which is currently the most efficient way to manage large amounts of data and query is implemented with powerful Structured Query Language (SQL). The search engine is written using Personal Home Page (PHP) with SQL embedded and web retrieval interface is developed for searching with Hypertext Markup Language (HTML). RESULTS: We present the first version of HBVPathDB, which is a HBV infection-related molecular interaction network database composed of 306 pathways with 1 050 molecules involved. With carefully drawn graphs, pathway information stored in HBVPathDB can be browsed in an intuitive way. We develop an easy-to-use interface for flexible accesses to the details of database. Convenient software is implemented to query and browse the pathway information of HBVPathDB. Four search page layout options-category search, gene search, description search, unitized search-are supported by the search engine of the database. The database is freely available at http://www.bio-inf.net/HBVPathDB/HBV/. CONCLUSION: The conventional perspective HBVPathDB have already contained a considerable amount of pathway information with HBV infection related, which is suitable for in-depth analysis of molecular interaction network of virus and host. HBVPathDB integrates pathway data-sets with convenient software for query, browsing, visualization, that provides users more opportunity to identify regulatory key molecules as potential drug targets and to explore the possible mechanism of HBV infection based on gene expression datasets.

Databases, Genetic↗
PubMed1999

Kleisli: a new tool for data integration in biology.

One of the central problems in bioinformatics is data retrieval and integration. The existing biological databases are geographically distributed across the Internet, complex and heterogeneous in data types and data structures, and constantly changing. With the current rapid growth of biomedical data, the challenge is how large volumes of data retrieved from multiple databases can be transformed and integrated automatically and flexibly. This article describes a powerful new tool, the Kleisli system, for complex queries across multiple databases and data integration.

Computational Biology↗
PubMed1993

ADAMS: Aggregate Data Management System for epidemiologists and health-care managers.

An effective health-care policy is supported by the availability of data in the form of statistical tables for epidemiologists and health-care managers. Creation, analysis and exploitation of these data strongly support the monitoring of trends in mortality and morbidity phenomena and the evaluation of offered health services. This might imply the transformation of statistical tables to more suitable formats. A successful management, manipulation and querying of a statistical table is a complex activity requiring a considerable knowledge of statistical problems. Computerised support can be precious in this task and this led to the development of several data management systems. In this paper we sketch out the features of ADAMS (Aggregate Data Management System), a system conceived to allow an easy interaction with statistical tables, reshaping and browsing of their descriptive part. ADAMS aims at simplifying the problem of extracting information from a statistical database and performing statistical table manipulation. The following functionalities are provided: definition of a statistical database at descriptive level; storage of data in the database; manipulation of data according to the summarisation and reclassification operators; browsing between data and their descriptive part. It also supports different manipulation styles according to different user profiles.

Data Interpretation, Statistical↗
PubMed2005

Recognizing names in biomedical texts using mutual information independence model and SVM plus sigmoid.

In this paper, we present a biomedical name recognition system, called PowerBioNE. In order to deal with the special phenomena in the biomedical domain, various evidential features are proposed and integrated through a mutual information independence model (MIIM). In addition, a support vector machine (SVM) plus sigmoid is proposed to resolve the data sparseness problem in the MIIM. In this way, the data sparseness problem in MIIM-based biomedical name recognition can be resolved effectively and a biomedical name recognition system with better performance and better portability can be achieved. Finally, we present two post-processing modules to deal with the nested entity name and abbreviation phenomena in the biomedical domain to further improve the performance. Evaluation shows that our system achieves F-measures of 69.1 and 71.2 on the 23 classes of GENIA V1.1 and V3.0, respectively. In particular, our system achieves an F-measure of 77.8 on the "protein" class of GENIA V3.0. It also shows that our system outperforms the best-reported system on GENIA V1.1 and V3.0.

Abstracting and Indexing↗
PubMed2003

Evaluation of ontology development tools for bioinformatics.

Ontologies are being used nowadays in many areas, including bioinformatics. To assist users in developing and maintaining ontologies a number of tools have been developed. In this paper we compare four such tools, Protégé-2000, Chimaera, DAG-Edit and OilEd. As test ontologies we have used ontologies from the Gene Ontology Consortium. No system is preferred in all situations, but each system has its own strengths and weaknesses.

Computational Biology↗
PubMed2001

GOBASE: the organelle genome database.

GOBASE (http://megasun.bch.umontreal.ca/gobase/) is a network-accessible biological database, which is unique in bringing together diverse biological data on organelles with taxonomically broad coverage, and in furnishing data that have been exhaustively verified and completed by experts. So far, we have focused on mitochondrial data: GOBASE contains all published nucleotide and protein sequences encoded by mitochondrial genomes, selected RNA secondary structures of mitochondria-encoded molecules, genetic maps of completely sequenced genomes, taxonomic information for all species whose sequences are present in the database and organismal descriptions of key protistan eukaryotes. All of these data have been integrated and organized in a formal database structure to allow sophisticated biological queries using terms that are inherent in biological concepts. Most importantly, data have been validated, completed, corrected and standardized, a prerequisite of meaningful analysis. In addition, where critical data are lacking, such as genetic maps and RNA secondary structures, they are generated by the GOBASE team and collaborators, and added to the database. The database is implemented in a relational database management system, but features an object-oriented view of the biological data through a Web/Genera-generated World Wide Web interface. Finally, we have developed software for database curation (i.e. data updates, validation and correction), which will be described in some detail in this paper.

Animals↗
PubMed2006

The Gene Ontology (GO) project in 2006.

The Gene Ontology (GO) project (http://www.geneontology.org) develops and uses a set of structured, controlled vocabularies for community use in annotating genes, gene products and sequences (also see http://song.sourceforge.net/). The GO Consortium continues to improve to the vocabulary content, reflecting the impact of several novel mechanisms of incorporating community input. A growing number of model organism databases and genome annotation groups contribute annotation sets using GO terms to GO's public repository. Updates to the AmiGO browser have improved access to contributed genome annotations. As the GO project continues to grow, the use of the GO vocabularies is becoming more varied as well as more widespread. The GO project provides an ontological annotation system that enables biologists to infer knowledge from large amounts of data.

Database Management Systems↗
PubMed2005

Integrated nuclear data utilisation system for innovative reactors.

A five-year research and development project on an integrated nuclear data utilisation system was initiated in 2002, for developing innovative nuclear energy systems such as accelerator-driven systems. The integrated nuclear data utilisation system will be constructed as a modular code system, which consists of two sub-systems: the nuclear data search and plotting sub-system, and the nuclear data processing and utilisation sub-system. The system will be operated with a graphical user interface in order to enable easy utilisation through the Internet by both nuclear design engineers and nuclear data evaluators. This paper presents an overview of the integrated nuclear data utilisation system, describes the development of a prototype system to examine the operability of the user interface and discusses specifications of the two sub-systems.

Computer Graphics↗
PubMed1994

HotList. Integration tools.

July's HotList features integration tools. Although many information systems vendors build custom interfaces or provide links to integrated systems, the focus of this Integration Tools HotList is to discover those companies who deliver truly useful tools for integrating disparate systems. All data provided by individual vendors responding to survey questions. Health Management Technology made every effort to contact all vendors within this market. Of 50 vendors contacted, 28 responded as offering integration tools. A full contact list may be requested by calling HMT editorial at (303) 220-0600. See The 1994 Health Management Technology Market Directory for complete listings.

Catalogs, Commercial as Topic↗
PubMed2002

A database system for the analysis of biochemical pathways.

To provide support for the analysis of biochemical pathways a database system based on a model that represents the characteristics of the domain is needed. This domain has proven to be difficult to model by using conventional data modelling techniques. We are building an ontology for biochemical pathways, which acts as the basis for the generation of a database on the same domain, allowing the definition of complex queries and complex data representation. The ontology is used as a modelling and analysis tool which allows the expression of complex semantics based on a first-order logic representation language. The induction capabilities of the system can help the scientist in formulating and testing research hypotheses that are difficult to express with the standard relational database mechanisms. An ontology representing the shared formalisation of the knowledge in a scientific domain can also be used as data integration tool clarifying the mapping of concepts to the developers of different databases. In this paper we describe the general structure of our system, concentrating on the ontology-based database as the key component of the system.

Biochemical Phenomena↗
PubMed2002

The Chronus II temporal database mediator.

Clinical databases typically contain a significant amount of temporal information. This information is often crucial in medical decision-support systems. Although temporal queries are common in clinical systems, the medical informatics field has no standard means for representing or querying temporal data. Over the past decade, the temporal database community has made a significant amount of progress in temporal systems. Much of this research can be applied to clinical database systems. This paper outlines a temporal database mediator called Chronus II. Chronus II extends the standard relational model and the SQL query language to support temporal queries. It provides an expressive general-purpose temporal query language that is tuned to the querying requirements of clinical decision support systems. This paper describes how we have used Chronus II to tackle a variety of clinical problems in decision support systems developed by our group.

Database Management Systems↗
PubMed2000

Common object request broker architecture (CORBA)-based security services for the virtual radiology environment.

The US Army Great Plains Regional Medical Command (GPRMC) has a requirement to conform to Department of Defense (DoD) and Army security policies for the Virtual Radiology Environment (VRE) Project. Within the DoD, security policy is defined as the set of laws, rules, and practices that regulate how an organization manages, protects, and distributes sensitive information. Security policy in the DoD is described by the Trusted Computer System Evaluation Criteria (TCSEC), Army Regulation (AR) 380-19, Defense Information Infrastructure Common Operating Environment (DII COE), Military Health Services System Automated Information Systems Security Policy Manual, and National Computer Security Center-TG-005, "Trusted Network Interpretation." These documents were used to develop a security policy that defines information protection requirements that are made with respect to those laws, rules, and practices that are required to protect the information stored and processed in the VRE Project. The goal of the security policy is to provide for a C2-level of information protection while also satisfying the functional needs of the GPRMC's user community. This report summarizes the security policy for the VRE and defines the CORBA security services that satisfy the policy. In the VRE, the information to be protected is embedded into three major information components: (1) Patient information consists of Digital Imaging and Communications in Medicine (DICOM)-formatted fields. The patient information resides in the digital imaging network picture archiving and communication system (DIN-PACS) networks in the database archive systems and includes (a) patient demographics; (b) patient images from x-ray, computed tomography (CT), magnetic resonance imaging (MRI), and ultrasound (US); and (c) prior patient images and related patient history. (2) Meta-Manager information to be protected consists of several data objects. This information is distributed to the Meta-Manager nodes and includes (a) radiologist schedules; (b) modality worklists; (c) routed case information; (d) DIN-PACS and Composite Health Care system (CHCS) messages, and Meta-Manager administrative and security information; and (e) patient case information. (3) Access control and communications security is required in the VRE to control who uses the VRE and Meta-Manager facilities and to secure the messages between VRE components. The CORBA Security Service Specification version 1.5 is designed to allow up to TCSEC's B2-level security for distributed objects. The CORBA Security Service Specification defines the functionality of several security features: identification and authentication, authorization and access control, security auditing, communication security, nonrepudiation, and security administration. This report describes the enhanced security features for the VRE and their implementation using commercial CORBA Security Service software products.

Artificial Intelligence↗
PubMed2003

Bioinformatics support for high-throughput proteomics.

In the "post-genome" era, mass spectrometry (MS) has become an important method for the analysis of proteome data. The rapid advancement of this technique in combination with other methods used in proteomics results in an increasing number of high-throughput projects. This leads to an increasing amount of data that needs to be archived and analyzed. To cope with the need for automated data conversion, storage, and analysis in the field of proteomics, the open source system ProDB was developed. The system handles data conversion from different mass spectrometer software, automates data analysis, and allows the annotation of MS spectra (e.g. assign gene names, store data on protein modifications). The system is based on an extensible relational database to store the mass spectra together with the experimental setup. It also provides a graphical user interface (GUI) for managing the experimental steps which led to the MS data. Furthermore, it allows the integration of genome and proteome data. Data from an ongoing experiment was used to compare manual and automated analysis. First tests showed that the automation resulted in a significant saving of time. Furthermore, the quality and interpretability of the results was improved in all cases.

Algorithms↗
PubMed1987

Reference master: a microcomputer-based storage and retrieval system for bibliographic references.

A complete system for housekeeping and retrieval of bibliographic references managing individual reprint collections is described. By the use of special hardware and individual data base software even large reprint collections in the range up to 65,000 papers are handled economically. A fast 8-bit microprocessor (HD 64180) in combination with a Winchester hard disk drive serves as the basis for rapid access to the desired information. An efficient string search algorithm written in assembly language guarantees a fast operation with a search speed of more than 6,000 entries/minute. The system cannot only prepare reference lists and reference files, but also incorporates an editor and maintains the control whether reprints are already on file or requested. The implementation of back-up schemes assure against data losses. Using a state of the art design single board computer and the most recent mass storage device technology, the system is as well small and cost effective, and thus suitable for personal use. In addition, some general questions and pitfalls concerning the management of scientific literature collections are touched upon.

Bibliographies as Topic↗