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The authors present a literature retrieval strategy for investigators who plan to conduct research on the Oklahoma City bombing. To facilitate a comprehensive review of the scholarly research on disasters, mass emergencies, and terrorism, a multidatabase search strategy is strongly encouraged. Secondly, a wealth of current information and data on the bombing are available on "popular" and "news" files.
MOTIVATION: The eXtensible Markup Language (XML) is an emerging standard for structuring documents, notably for the World Wide Web. In this paper, the authors present XML and examine its use as a data language for bioinformatics. In particular, XML is compared to other languages, and some of the potential uses of XML in bioinformatics applications are presented. The authors propose to adopt XML for data interchange between databases and other sources of data. Finally the discussion is illustrated by a test case of a pedigree data model in XML. CONTACT: Emmanuel.Barillot@infobiogen.fr
The Molecular Biology Database Collection represents an effort geared at making molecular biology database resources more accessible to biologists. This online resource, available at http://www.oup.co.uk/nar/Volume_28/Issue_01/html /gkd115_gml.html, is intended to serve as a searchable, up-to-date, centralized jumping-off point to individual Web sites. An emphasis has also been placed on including databases where new value is added to the underlying data by virtue of curation, new data connections, or other innovative approaches.
Undulator X-ray sources on third-generation synchrotrons have pushed small-angle X-ray scattering (SAXS) to the forefront of techniques in nanoscience and technology. With higher X-ray fluxes and improved focusing, it is usually the scattered intensity detector that places the most serious limitations on the overall capabilities of the instrument. Incorporating relatively simple components like point detectors, scattering standards, masking filters and in-line sample visualization into the flight tube of a pinhole-geometry SAXS camera can do much to mitigate these limitations. How these enhancements can be incorporated into routine data collection is demonstrated on the ChemMatCARS SAXS instrument, which utilizes pinhole geometry with an undulator insertion device at sector 15 of the Advanced Photon Source. In addition, with an X-ray energy range of 6-32 keV (2.0-0.4 A) and an energy resolution of 10(-4) DeltaE/E, this instrument can measure anomalous SAXS over a wide variety of atom species, with reliable normalization of scattered data.
This paper reports excellent results with respect to application of optical cards in medical care, based on improvements in the technology for encoding optical cards and devices used to increase read-write speed, and also reports the issuance of the first Japanese standards for the data format of optical cards.
We describe an algorithm for context-based segmentation of visual data. New frames in an image sequence (video) are segmented based on the prior segmentation of earlier frames in the sequence. The segmentation is performed by adapting a probabilistic model learned on previous frames, according to the content of the new frame. We utilize the maximum a posteriori version of the EM algorithm to segment the new image. The Gaussian mixture distribution that is used to model the current frame is transformed into a conjugate-prior distribution for the parametric model describing the segmentation of the new frame. This semisupervised method improves the segmentation quality and consistency and enables a propagation of segments along the segmented images. The performance of the proposed approach is illustrated on both simulated and real image data.
Near-field signal-redundancy (NFSR) algorithms for phase-aberration correction have been proposed and experimentally tested for linear and phased one-dimensional arrays. In this paper the performance of an all-row-plus-two-column, two-dimensional algorithm has been analyzed and tested with simulated data sets. This algorithm applies the NFSR algorithm for one-dimensional arrays to all the rows as well as the first and last columns of the array. The results from the two column measurements are used to derive a linear term for each row measurement result. These linear terms then are incorporated into the row results to obtain a two-dimensional phase aberration profile. The ambiguity phase aberration profile, which is the difference between the true and the derived phase aberration profiles, of this algorithm is not linear. Two methods, a trial-and-error method and a diagonal-measurement method, are proposed to linearize the ambiguity profile. The performance of these algorithms is analyzed and tested with simulated data sets.
Visualization tools are typically evaluated in controlled studies that observe the short-term usage of these tools by participants on preselected data sets and benchmark tasks. Though such studies provide useful suggestions, they miss the long-term usage of the tools. A longitudinal study of a bioinformatics data set analysis is reported here. The main focus of this work is to capture the entire analysis process that an analyst goes through from a raw data set to the insights sought from the data. The study provides interesting observations about the use of visual representations and interaction mechanisms provided by the tools, and also about the process of insight generation in general. This deepens our understanding of visual analytics, guides visualization developers in creating more effective visualization tools in terms of user requirements, and guides evaluators in designing future studies that are more representative of insights sought by users from their data sets.
NUD.IST 3.0 was generally effective in managing the qualitative data of dyspnea stimuli. Yet, some disadvantages were found related to format restrictions of transcripts and data volume. In particular, an appropriate format of transcripts for NUD.IST use was critical for efficient data management. Awareness of strengths and limitations of program functions is necessary to use NUD.IST efficiently in qualitative data management.
BACKGROUND: Sequence comparison is one of the most prominent tools in biological research, and is instrumental in studying gene function and evolution. The rapid development of high-throughput technologies for measuring protein interactions calls for extending this fundamental operation to the level of pathways in protein networks. RESULTS: We present a comprehensive framework for protein network searches using pathway queries. Given a linear query pathway and a network of interest, our algorithm, QPath, efficiently searches the network for homologous pathways, allowing both insertions and deletions of proteins in the identified pathways. Matched pathways are automatically scored according to their variation from the query pathway in terms of the protein insertions and deletions they employ, the sequence similarity of their constituent proteins to the query proteins, and the reliability of their constituent interactions. We applied QPath to systematically infer protein pathways in fly using an extensive collection of 271 putative pathways from yeast. QPath identified 69 conserved pathways whose members were both functionally enriched and coherently expressed. The resulting pathways tended to preserve the function of the original query pathways, allowing us to derive a first annotated map of conserved protein pathways in fly. CONCLUSION: Pathway homology searches using QPath provide a powerful approach for identifying biologically significant pathways and inferring their function. The growing amounts of protein interactions in public databases underscore the importance of our network querying framework for mining protein network data.
BACKGROUND: Gene Ontology (GO) terms are often used to assess the results of microarray experiments. The most common way to do this is to perform Fisher's exact tests to find GO terms which are over-represented amongst the genes declared to be differentially expressed in the analysis of the microarray experiment. However, due to the high degree of dependence between GO terms, statistical testing is conservative, and interpretation is difficult. RESULTS: We propose testing groups of GO terms rather than individual terms, to increase statistical power, reduce dependence between tests and improve the interpretation of results. We use the publicly available package POSOC to group the terms. Our method finds groups of GO terms significantly over-represented amongst differentially expressed genes which are not found by Fisher's tests on individual GO terms. CONCLUSION: Grouping Gene Ontology terms improves the interpretation of gene set enrichment for microarray data.
Exchanging and integration of patient data across heterogeneous databases and institutional boundaries offers many problems. We focused on two issues: (1) how to identify identical patients between different systems and institutions while lacking universal patient identifiers; and (2) how to link patient data across heterogeneous databases and institutional boundaries. To solve these problems, we created a patient identification (ID) translation model and a dynamic linking method in the Common Object Request Broker Architecture (CORBA) environment. The algorithm for the patient ID translation is based on patient attribute matching plus computer-based human checking; the method for dynamic linking is temporal mapping. By implementing these methods into computer systems with help of the distributed object computing technology, we built a prototype of a CORBA-based object framework in which the patient ID translation and dynamic linking methods were embedded. Our experiments with a Web-based user interface using the object framework and dynamic linking-through the object framework were successful. These methods are important for exchanging and integrating patient data across heterogeneous databases and institutional boundaries.
We discuss an approach towards integrating heterogeneous nervous system data using an augmented Entity-Attribute-Value (EAV) schema design. This approach, widely used in implementing electronic patient record systems (EPRSs), allows the physical schema of the database to be relatively immune to changes in domain knowledge. This is because new kinds of facts are added as data (or as metadata) rather than hard-coded as the names of newly created tables or columns. Because the domain knowledge is stored as metadata, a framework developed in one scientific domain can be ported to another with only modest revision. We describe our progress in creating a code framework that handles browsing and hyperlinking of the different kinds of data.
Presently, there is a growing demand from the healthcare community to leverage upon and transform the vast quantities of healthcare data into value-added, 'decision-quality' knowledge, vis-à-vis, strategic knowledge services oriented towards healthcare management and planning. To meet this end, we present a Strategic Knowledge Services Info-structure that leverages on existing healthcare knowledge/data bases to derive decision-quality knowledge-knowledge that is extracted from healthcare data through services akin to knowledge discovery in databases and data mining.
Despite a quarter century of developments, few specialists directly use a computerized patient record, that fully replaces the paper chart. Because of the diversity of domains in specialized care, medical decision-making and the continuity of care may suffer from scattering of patient data over various records. The challenge was to develop a computerized patient record, that would be versatile enough to tailor it to specific needs, while keeping it uniform enough to permit physicians to share data on the same patient. In our CPR, the key that reconciles versatility with uniformity lies in the design of the data model. The CPR consists of a mother record with specialized sub-records, that all share the same data model. A physician can enlarge his scope for decision-making by consulting other specialized records on the same patient or by viewing the combined information of all sub-records without the need to convert data or to familiarize himself with different interfaces.
The International Network of Food Data Systems planning conference recommends establishing nomenclature and a system of coding for use in INFOODS. The International Food Naming System would facilitate collection, tabulation, storing, and retrieval of information. The system consists of two files for each food: one describing the name in a standardized manner and another reporting chemical and biological data. The two files are linked by International Food Number (IFN). Food names consist of controlled terms called facets: origin, part, process, stage of maturity, and grade. Within each facet, such elements as genus, species, variety (scientific name) and generic name, breed or kind, and strain (English name) are defined. Elements are assigned numerical codes to facilitate sorting and storage. Carefully defined standard descriptions are used in each facet. Each descriptor is assigned an alphabetic code, an unlimited number allowing an open-ended flexible system. IFN may be incorporated into a computerized data management system and stored data searched and sorted for information retrieval on given parameters, e.g., country, state, laboratory, or kind of package. Data can be summarized to obtain averages, ranges, and standard deviations. Summarized data, linked with the International Food Names by the IFN, may be printed out in desired format.
Modern information technology offers efficiencies in medical practice, with a reduction in secretarial time in maintaining, filing and retrieving the paper medical record. Electronic requesting of investigations allows tracking of outstanding results. Less storage space is required and telephone calls from pharmacies, pathology and medical imaging service providers to clarify the hand-written request are abolished. Voice recognition software reduces secretarial typing time per letter. These combined benefits can lead to significantly reduced costs and improved patient care. The paperless office is possible, but requires commitment and training of all staff; it is preferable but not absolutely essential that at least one member of the practice has an interest and some expertise in computers. More importantly, back-up from information technology providers and back-up of the electronic data are absolutely crucial and a paperless environment should not be considered without them.
The storage objectives for the healthcare enterprise (HE) are to ensure that information (images and data) are readily available anywhere and at anytime, images and data are secure, and the storage fulfills legal requirements and the Health Insurance Portability and Accountability Act (HIPAA). These objectives must be satisfied at a minimum economic cost with respect to personnel, hardware, software, space and telecommunications. Many approaches and storage configurations meet these objectives. Which approach is chosen will depend on the size of the institution, patient population, geographic distribution of the institutions (if more than one), type of facility (such as a hospital, outpatient clinic or private imaging center), and financial investment objectives. The quantity of storage required depends on the characteristics of the modalities, the number of imaging devices and databases, the number and location of imaging sites that make up the HE, the size of the data and image, and the projected procedure volume growth. The only certainty with respect to storage requirements is that they will increase significantly with time. The types of storage required in the HE can be described by their functions: Active storage includes both online and long-term storage. Backup images are temporarily backed up on the limited storage capacity of the modality for several days or longer. Additional copies of the study are made on different media (e.g., disk, DVD or tape), in different locations. The process of backing up data and images must be automated. Effective April 21, 2005, HIPAA requires that all healthcare entities have a disaster recovery plan in effect. This requires that a copy of all medical data be secure, retrievable and maintained in a second location, such that if the primary copy of the data is destroyed or made unavailable, the disaster recovery copy would be available. Planning for the HE archive is critical if the HE is to work productively in an integrated digital environment. The information technology department must be an integral part of planning for the HE archive, which must be located in a secure data center and not under the management of any single clinical department. After the technologies currently available are evaluated, it is imperative that the chosen solution is cost-effective and scalable, and that it will allow the HE to take advantage of future storage and storage management technology.