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PubMed1988

StrateGene: object-oriented programming in molecular biology.

This paper describes some of the ways that object-oriented programming methodologies have been used to represent and manipulate biological information in a working application. When running on a Xerox 1100 series computer, StrateGene functions as a genetic engineering workstation for the management of information about cloning experiments. It represents biological molecules, enzymes, fragments, and methods as classes, subclasses, and members in a hierarchy of objects. These objects may have various attributes, which themselves can be defined and classified. The attributes and their values can be passed from the classes of objects down to the subclasses and members. The user can modify the objects and their attributes while using them. New knowledge and changes to the system can be incorporated relatively easily. The operations on the biological objects are associated with the objects themselves. This makes it easier to invoke them correctly and allows generic operations to be customized for the particular object.

Cloning, Molecular↗

PubMed2005

[Teleradiology and PACS--strategy of the Innsbruck University Hospital].

Systems for management of digital imaging data are very important and widespread at the Innsbruck University Hospital and constitute a central component of the IT strategies followed by the hospital operating company TILAK (Tyrolean public hospitals). The particular goal is to integrate all imaging data into the electronic medical records and make these available online to each of the approx. 2500 clinic workstations and ensure electronic data exchange with other healthcare services. Teleradiology connections have been established at the University Clinic for Radiology since 1995; these have been continually expanded and linked to the central PACS. An eHealth web portal was recently established to facilitate transfer of images and findings from TILAK hospitals to other healthcare organizations. Registered users can be cleared for a limited time to access all radiological imaging data via this web portal.

Austria↗

PubMed2004

Extracting human protein interactions from MEDLINE using a full-sentence parser.

MOTIVATION: The living cell is a complex machine that depends on the proper functioning of its numerous parts, including proteins. Understanding protein functions and how they modify and regulate each other is the next great challenge for life-sciences researchers. The collective knowledge about protein functions and pathways is scattered throughout numerous publications in scientific journals. Bringing the relevant information together becomes a bottleneck in a research and discovery process. The volume of such information grows exponentially, which renders manual curation impractical. As a viable alternative, automated literature processing tools could be employed to extract and organize biological data into a knowledge base, making it amenable to computational analysis and data mining. RESULTS: We present MedScan, a completely automated natural language processing-based information extraction system. We have used MedScan to extract 2976 interactions between human proteins from MEDLINE abstracts dated after 1988. The precision of the extracted information was found to be 91%. Comparison with the existing protein interaction databases BIND and DIP revealed that 96% of extracted information is novel. The recall rate of MedScan was found to be 21%. Additional experiments with MedScan suggest that MEDLINE is a unique source of diverse protein function information, which can be extracted in a completely automated way with a reasonably high precision. Further directions of the MedScan technology improvement are discussed. AVAILABILITY: MedScan is available for commercial licensing from Ariadne Genomics, Inc.

Abstracting and Indexing↗

PubMed2005

Ranking the whole MEDLINE database according to a large training set using text indexing.

BACKGROUND: The MEDLINE database contains over 12 million references to scientific literature, with about 3/4 of recent articles including an abstract of the publication. Retrieval of entries using queries with keywords is useful for human users that need to obtain small selections. However, particular analyses of the literature or database developments may need the complete ranking of all the references in the MEDLINE database as to their relevance to a topic of interest. This report describes a method that does this ranking using the differences in word content between MEDLINE entries related to a topic and the whole of MEDLINE, in a computational time appropriate for an article search query engine. RESULTS: We tested the capabilities of our system to retrieve MEDLINE references which are relevant to the subject of stem cells. We took advantage of the existing annotation of references with terms from the MeSH hierarchical vocabulary (Medical Subject Headings, developed at the National Library of Medicine). A training set of 81,416 references was constructed by selecting entries annotated with the MeSH term stem cells or some child in its sub tree. Frequencies of all nouns, verbs, and adjectives in the training set were computed and the ratios of word frequencies in the training set to those in the entire MEDLINE were used to score references. Self-consistency of the algorithm, benchmarked with a test set containing the training set and an equal number of references randomly selected from MEDLINE was better using nouns (79%) than adjectives (73%) or verbs (70%). The evaluation of the system with 6,923 references not used for training, containing 204 articles relevant to stem cells according to a human expert, indicated a recall of 65% for a precision of 65%. CONCLUSION: This strategy appears to be useful for predicting the relevance of MEDLINE references to a given concept. The method is simple and can be used with any user-defined training set. Choice of the part of speech of the words used for classification has important effects on performance. Lists of words, scripts, and additional information are available from the web address http://www.ogic.ca/projects/ks2004/.

Abstracting and Indexing↗

PubMed2005

Statistical Viewer: a tool to upload and integrate linkage and association data as plots displayed within the Ensembl genome browser.

BACKGROUND: To facilitate efficient selection and the prioritization of candidate complex disease susceptibility genes for association analysis, increasingly comprehensive annotation tools are essential to integrate, visualize and analyze vast quantities of disparate data generated by genomic screens, public human genome sequence annotation and ancillary biological databases. We have developed a plug-in package for Ensembl called "Statistical Viewer" that facilitates the analysis of genomic features and annotation in the regions of interest defined by linkage analysis. RESULTS: Statistical Viewer is an add-on package to the open-source Ensembl Genome Browser and Annotation System that displays disease study-specific linkage and/or association data as 2 dimensional plots in new panels in the context of Ensembl's Contig View and Cyto View pages. An enhanced upload server facilitates the upload of statistical data, as well as additional feature annotation to be displayed in DAS tracts, in the form of Excel Files. The Statistical View panel, drawn directly under the ideogram, illustrates lod score values for markers from a study of interest that are plotted against their position in base pairs. A module called "Get Map" easily converts the genetic locations of markers to genomic coordinates. The graph is placed under the corresponding ideogram features a synchronized vertical sliding selection box that is seamlessly integrated into Ensembl's Contig- and Cyto- View pages to choose the region to be displayed in Ensembl's "Overview" and "Detailed View" panels. To resolve Association and Fine mapping data plots, a "Detailed Statistic View" plot corresponding to the "Detailed View" may be displayed underneath. CONCLUSION: Features mapping to regions of linkage are accentuated when Statistic View is used in conjunction with the Distributed Annotation System (DAS) to display supplemental laboratory information such as differentially expressed disease genes in private data tracks. Statistic View is a novel and powerful visual feature that enhances Ensembl's utility as valuable resource for integrative genomic-based approaches to the identification of candidate disease susceptibility genes. At present there are no other tools that provide for the visualization of 2-dimensional plots of quantitative data scores against genomic coordinates in the context of a primary public genome annotation browser.

Chromosome Mapping↗

PubMed2005

ONTOFUSION: ontology-based integration of genomic and clinical databases.

ONTOFUSION is an ontology-based system designed for biomedical database integration. It is based on two processes: mapping and unification. Mapping is a semi-automated process that uses ontologies to link a database schema with a conceptual framework-named virtual schema. There are three methodologies for creating virtual schemas, according to the origin of the domain ontology used: (1) top-down--e.g. using an existing ontology, such as the UMLS or Gene Ontology--, (2) bottom-up--building a new domain ontology-- and (3) a hybrid combination. Unification is an automated process for integrating ontologies and hence the database to which they are linked. Using these methods, we employed ONTOFUSION to integrate a large number of public genomic and clinical databases, as well as biomedical ontologies.

Data Collection↗

PubMed2002

UniBLAST: a system to filter, cluster, and display BLAST results and assign unique gene annotation.

MOTIVATION: More and more often, a gene is epitomized by a large number of sequences in GenBank. This high redundancy makes it very difficult to identify a unique best match for a query sequence from its BLAST results. We developed a novel program UniBLAST that filters out uninformative hits, clusters the redundant hits, groups the hits by LocusLink, and graphically displays the results. We also implemented a scoring function in UniBLAST to assign a unique gene name to a query sequence. UniBLAST significantly increases the efficiency of gene annotation. AVAILABILITY: The program is available at http://south.genomics.org.cn/software/uniblast/index.html CONTACT: uniblast@genomics.org.cn; wei@nexusgenomics.com

Cluster Analysis↗

PubMed2003

[Establishment and effect of the drug safety management monitoring system].

Early detection and early treatment of adverse drug reactions have recently become more important. It is natural that physicians should treat adverse drug reactions carefully, but it is also important to establish a system for their early systematic detection and treatment. Therefore, by comparing current data with that preserved in our clinical laboratory's data management registry and identifying values significantly different from earlier values, we established a screening system for any condition which may have a possible relationship with drugs and feeds back the results to the physician(s) in charge (drug safety management monitoring system). The effectiveness of the system was then evaluated. The subjects were outpatients who visited the Diabetes Endocrine Metabolism Center of our hospital during a six-month period. Cases where the possibility of a relationship between abnormal changes of laboratory data and drugs was not ruled out were reported to the attending physician using a drug safety monitoring report form. In 14 of 34 cases reported, a relationship with drugs could not be ruled out. Two of these 14 cases were reported to the Ministry of Health, Labour and Welfare because they were serious. Therefore, it was concluded that this system was useful for early detection of adverse reactions.

Adverse Drug Reaction Reporting Systems↗

PubMed2005

Intelligent client for integrating bioinformatics services.

MOTIVATION: In addition to existing bioinformatics software, a lot of new tools are being developed world wide to supply services for an ever growing, widely dispersed and heterogeneous collection of biological data. The integration of these resources under a common platform is a challenging task. To this end, several groups are developing integration technologies, in which services are usually registered in some sort of catalogue to allow novel discovering and accessing mechanisms to be implemented. However, each service demands specific interfaces to accommodate their parameters and it is a complicated task linking the different service inputs and outputs to solve a biological problem. RESULTS: In this work we address the design and implementation of a versatile web client to access BioMOBY compatible services (a system by which a client can interact with multiple sources of biological data regardless of the underlying format or schema) using the service description stored in the BioMOBY catalogue. The automatic interface generator significantly reduces developing time and produces uniform service access mechanisms. The design and proof of concept (for such a client) including the generic interface generator have been developed and implemented in the National Institute for Bioinformatics in Spain. AVAILABILITY: The INB (National Institute for Bioinformatics, Spain) platform is available at www.inab.org/MOWServ

Automation↗

PubMed2005

VIS-O-BAC: exploratory visualization of functional genome studies from bacteria.

UNLABELLED: The visualization-aided exploration of complex datasets will allow the research community to formulate novel functional hypotheses leading to a better understanding of biological processes at all levels. Therefore, we have developed a web resource termed VIS-O-BAC designed for the functional investigation of expression data for model systems, such as bacterial pathogens based on a graphical display. Genome-scale datasets derived from typical 'omic' approaches can directly be explored with respect to three biologically relevant aspects, the genome structure (operon organization), the organization of genes in pathways (KEGG) and the gene function with Gene Ontology (GO) terms. The integrated viewers can be used in parallel and combine expression data and functional annotations from different external data repositories. The graphical visualizations evidently accelerate both the validation of regulatory information and the detection of affected biological processes. AVAILABILITY: http://leger2.gbf.de/cgi-bin/vis-o-bac.pl. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Chromosome Mapping↗

PubMed2004

Bioie: retargetable information extraction and ontological annotation of biological interactions from the literature.

The need for extracting general biological interactions of arbitrary types from the rapidly growing volume of the biomedical literature is drawing increased attention, while the need for this much diversity also requires both a robust treatment of complex linguistic phenomena and a method to consistently characterize the results. We present a biomedical information extraction system, BioIE, to address both of these needs by utilizing a full-fledged English grammar formalism, or a combinatory categorial grammar, and by annotating the results with the terms of Gene Ontology, which provides a common and controlled vocabulary. BioIE deals with complex linguistic phenomena such as coordination, relative structures, acronyms, appositive structures, and anaphoric expressions. In order to deal with real-world syntactic variations of ontological terms, BioIE utilizes the syntactic dependencies between words in sentences as well, based on the observation that the component words in an ontological term usually appear in a sentence with known patterns of syntactic dependencies.

Abstracting and Indexing↗

PubMed2003

Recent developments in the PHENIX software for automated crystallographic structure determination.

A new software system called PHENIX (Python-based Hierarchical ENvironment for Integrated Xtallography) is being developed for the automation of crystallographic structure solution. This will provide the necessary algorithms to proceed from reduced intensity data to a refined molecular model, and facilitate structure solution for both the novice and expert crystallographer. Here, the features of PHENIXare reviewed and the recent advances in infrastructure and algorithms are briefly described.

Algorithms↗

PubMed2005

[Digital teaching archive. Concept, implementation, and experiences in a university setting].

Film-based teaching files require a substantial investment in human, logistic, and financial resources. The combination of computer and network technology facilitates the workflow integration of distributing radiologic teaching cases within an institution (intranet) or via the World Wide Web (Internet). A digital teaching file (DTF) should include the following basic functions: image import from different sources and of different formats, editing of imported images, uniform case classification, quality control (peer review), a controlled access of different user groups (in-house and external), and an efficient retrieval strategy. The portable network graphics image format (PNG) is especially suitable for DTFs because of several features: pixel support, 2D-interlacing, gamma correction, and lossless compression. The American College of Radiology (ACR) "Index for Radiological Diagnoses" is hierarchically organized and thus an ideal classification system for a DTF. Computer-based training (CBT) in radiology is described in numerous publications, from supplementing traditional learning methods to certified education via the Internet. Attractiveness of a CBT application can be increased by integration of graphical and interactive elements but makes workflow integration of daily case input more difficult. Our DTF was built with established Internet instruments and integrated into a heterogeneous PACS/RIS environment. It facilitates a quick transfer (DICOM_Send) of selected images at the time of interpretation to the DTF and access to the DTF application at any time anywhere within the university hospital intranet employing a standard web browser. A DTF is a small but important building block in an institutional strategy of knowledge management.

Computer-Assisted Instruction↗

PubMedDate not supplied

A framework for querying a database for structural information on 3D images of macromolecules: A web-based query-by-content prototype on the BioImage macromolecular server.

Nowadays we are experiencing a remarkable growth in the number of databases that have become accessible over the Web. However, in a certain number of cases, for example, in the case of BioImage, this information is not of a textual nature, thus posing new challenges in the design of tools to handle these data. In this work, we concentrate on the development of new mechanisms aimed at "querying" these databases of complex data sets by their intrinsic content, rather than by their textual annotations only. We concentrate our efforts on a subset of BioImage containing 3D images (volumes) of biological macromolecules, implementing a first prototype of a "query-by-content" system. In the context of databases of complex data types the term query-by-content makes reference to those data modeling techniques in which user-defined functions aim at "understanding" (to some extent) the informational content of the data sets. In these systems the matching criteria introduced by the user are related to intrinsic features concerning the 3D images themselves, hence, complementing traditional queries by textual key words only. Efficient computational algorithms are required in order to "extract" structural information of the 3D images prior to storing them in the database. Also, easy-to-use interfaces should be implemented in order to obtain feedback from the expert. Our query-by-content prototype is used to construct a concrete query, making use of basic structural features, which are then evaluated over a set of three-dimensional images of biological macromolecules. This experimental implementation can be accessed via the Web at the BioImage server in Madrid, at http://www.bioimage.org/qbc/index.html.

Animals↗

PubMed2004

CBS Genome Atlas Database: a dynamic storage for bioinformatic results and sequence data.

UNLABELLED: Currently, new bacterial genomes are being published on a monthly basis. With the growing amount of genome sequence data, there is a demand for a flexible and easy-to-maintain structure for storing sequence data and results from bioinformatic analysis. More than 150 sequenced bacterial genomes are now available, and comparisons of properties for taxonomically similar organisms are not readily available to many biologists. In addition to the most basic information, such as AT content, chromosome length, tRNA count and rRNA count, a large number of more complex calculations are needed to perform detailed comparative genomics. DNA structural calculations like curvature and stacking energy, DNA compositions like base skews, oligo skews and repeats at the local and global level are just a few of the analysis that are presented on the CBS Genome Atlas Web page. Complex analysis, changing methods and frequent addition of new models are factors that require a dynamic database layout. Using basic tools like the GNU Make system, csh, Perl and MySQL, we have created a flexible database environment for storing and maintaining such results for a collection of complete microbial genomes. Currently, these results counts to more than 220 pieces of information. The backbone of this solution consists of a program package written in Perl, which enables administrators to synchronize and update the database content. The MySQL database has been connected to the CBS web-server via PHP4, to present a dynamic web content for users outside the center. This solution is tightly fitted to existing server infrastructure and the solutions proposed here can perhaps serve as a template for other research groups to solve database issues. AVAILABILITY: A web based user interface which is dynamically linked to the Genome Atlas Database can be accessed via www.cbs.dtu.dk/services/GenomeAtlas/. SUPPLEMENTARY INFORMATION: This paper has a supplemental information page which links to the examples presented: www.cbs.dtu.dk/services/GenomeAtlas/suppl/bioinfdatabase.

Algorithms↗

PubMedDate not supplied

Partners HealthCare. Creating and managing an integrated delivery system.

Supporting the "integration" of an integrated delivery system is an exceptionally complex and difficult challenge. Lack of organizational clarity about integration strategies and value, political challenges in effecting integration, the idiosyncratic and evolutionary nature of integration, and the technical challenges of integrating heterogeneous technologies all contribute to the scale of the challenge. Information systems integration strategies and tactics should be guided by overall concepts that frame the organization's understanding of the nature of integration. Effort must be directed to working with IDS leadership to define the approach to specific classes of integration, e.g., clinical integration. And, as always, one should learn from the experiences of others. While it may be difficult to fully define the value of integration in an IDS, the IDS seems to be a permanent feature of the healthcare landscape. And the integration of the IDS has value, value that is often nuanced, intangible, and complicated. Hence, the efficient and effective application of information systems to further integration is a critical organizational undertaking.

Computer Communication Networks↗

PubMed1991

SISCOPE: a multiuser information system for gastrointestinal endoscopy.

SISCOPE is an integrated data management system for use in gastrointestinal endoscopy units which operates in the multiuser mode on UNIX minicomputers or MS-DOS personal computers and can be used for patient bookings, endoscopic data entry and retrieval, and automatic report generation in upper gastrointestinal endoscopy, proctologic examinations, colonoscopy and peritoneoscopy. The description of endoscopic findings is remarkably detailed and data entry very rapid due to an advanced design of input screens that incorporates several recent concepts, including windows, menu bars and pull-down menus; typing is eliminated as data is entered with a mouse by pointing at options within menus. Endoscopic findings can be described under eight headings: morphology, topography, qualifiers, modifiers, signs of bleeding, endoscopic diagnosis, pathological diagnosis and etiology. Terminology is based strictly 3on the OMED system. SISCOPE also allows recording of details on endoscopic procedures, indications for the examination, preparation, premedication, complications and late entry of pathology reports. After entering all data, a report in natural language is produced automatically, the entire process taking one minute on average. Data retrieval programs give on-line access to previous examinations of a given patient and automatically generate activity reports. A formal language allows direct queries to the database and transfer of data for statistical analysis or other data processing. The system is simple to learn and use because operation is intuitive and all endoscopic techniques share the same basic menu structure and screen design.

Computer Systems↗

PubMed2005

Concept-based annotation of enzyme classes.

MOTIVATION: Given the explosive growth of biomedical data as well as the literature describing results and findings, it is getting increasingly difficult to keep up to date with new information. Keeping databases synchronized with current knowledge is a time-consuming and expensive task-one which can be alleviated by automatically gathering findings from the literature using linguistic approaches. We describe a method to automatically annotate enzyme classes with disease-related information extracted from the biomedical literature for inclusion in such a database. RESULTS: Enzyme names for the 3901 enzyme classes in the BRENDA database, a repository for quantitative and qualitative enzyme information, were identified in more than 100,000 abstracts retrieved from the PubMed literature database. Phrases in the abstracts were assigned to concepts from the Unified Medical Language System (UMLS) utilizing the MetaMap program, allowing for the identification of disease-related concepts by their semantic fields in the UMLS ontology. Assignments between enzyme classes and diseases were created based on their co-occurrence within a single sentence. False positives could be removed by a variety of filters including minimum number of co-occurrences, removal of sentences containing a negation and the classification of sentences based on their semantic fields by a Support Vector Machine. Verification of the assignments with a manually annotated set of 1500 sentences yielded favorable results of 92% precision at 50% recall, sufficient for inclusion in a high-quality database. AVAILABILITY: Source code is available from the author upon request. SUPPLEMENTARY INFORMATION: ftp.uni-koeln.de/institute/biochemie/pub/brenda/info/diseaseSupp.pdf.

Algorithms↗