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For the conversion of nonstructural chemical databases to structure databases, a series of algorithms to find the closest match between existing names to names in a reference database are described. On the basis of the best match, new fields such as the Chemical Abstracts Service Registry Number (CASRN) or structures were added to the database.
Conventional methods of gene prediction rely on the recognition of DNA-sequence signals, the coding potential or the comparison of a genomic sequence with a cDNA, EST, or protein database. Reasons for limited accuracy in many circumstances are species-specific training and the incompleteness of reference databases. Lately, comparative genome analysis has attracted increasing attention. Several analysis tools that are based on human/mouse comparisons are already available. Here, we present a program for the prediction of protein-coding genes, termed SGP-1 (Syntenic Gene Prediction), which is based on the similarity of homologous genomic sequences. In contrast to most existing tools, the accuracy of depends little on species-specific properties such as codon usage or the nucleotide distribution. may therefore be applied to nonstandard model organisms in vertebrates as well as in plants, without the need for extensive parameter training. In addition to predicting genes in large-scale genomic sequences, the program may be useful to validate gene structure annotations from databases. To this end, SGP-1 output also contains comparisons between predicted and annotated gene structures in HTML format. The program can be accessed via a Web server at http://soft.ice.mpg.de/sgp-1. The source code, written in ANSI C, is available on request from the authors.
Direct automated cycle sequencing (DACS) of a reverse transcription-polymerase chain reaction (RT-PCR) product of the S-1 subunit of the spike peplomer gene was used to identify infectious bronchitis virus (IBV) serotypes. Degenerate primers CK4 and CK2, utilized previously in our laboratory, were selected for DACS because they successfully amplify a wide range of serotypes represented by various reference strains and field isolates and the resulting polymerase chain reaction (PCR) product contains diagnostically relevant S-1 sequences that can be used to identify the serotype of IBV. The S-1 nucleotide sequences generated by DACS were aligned and analyzed with commercial software to determine their relationship to the S-1 nucleotide sequences of IBV strains on deposit in the GenBank and EMBL databases. Reference strains Massachusetts (Mass) 41, Connecticut (Conn), Arkansas (Ark) DPI, JMK, and DE/072/92 were initially tested by DACS to establish the feasibility of the procedure. The DACS procedure was further evaluated with a panel of "unknowns" comprised of IBV reference strains, field isolates, and variant serotypes collected by our laboratory. The DACS procedure provided high-quality and reproducible S-1 sequence for all IBV serotypes tested, including variant serotypes that had not been sequenced previously. The S-1 nucleotide sequences for the amplified PCR products of reference strains Mass 41, Conn, Ark DPI, JMK, and DE/072/92 generated by DACS were highly homologous (>99% nucleotide identity) with their respective GenBank database sequences. In the unknown panel, the nucleotide identities of the DACS S-1 sequences of field isolates of serotypes previously identified by virus neutralization were also found to be very high (> or = 95.5%) after alignment with database sequences. In contrast, the nucleotide identities of S-1 sequences of variant serotypes 37, 3330, and PA/1220/98 and reference strain Clark 333, for which database sequences were not available, ranged from 27.7% to 73.8%, well below the identity values for a homologous serotype. With alignment software, the identities of strains in mixtures of RNAs of two different serotypes were not resolvable. DACS of IBV S-1 RT-PCR products will enable researchers to rapidly identify field strains, including new, previously unrecognized variant virus serotypes.
OBJECTIVE: Dual-energy x-ray absorptiometry (DEXA) is increasingly used to evaluate children for osteoporosis. However, the interpretation of pediatric DEXA is complicated by growth and development. Because most DEXA scans are performed on adults, we hypothesized that physicians who interpret DEXA may not be aware of these pediatric issues, potentially leading to misdiagnosis. STUDY DESIGN: Children (n=34, aged 4-17 years) diagnosed with low bone mineral density (BMD) based on a DEXA scan were referred for possible inclusion in a childhood osteoporosis protocol. The referral DEXA scans were analyzed for accuracy. RESULTS: Thirty (88%) of the scans had at least one error in interpretation. The most frequent error (62%) was use of T-score (SD score compared with young adults) to diagnose osteoporosis, which is inappropriate for children. Other errors included use of a reference database that does not consider gender or ethnic differences (21%), incorrect bone map (21%), inattention to short stature (15%), and other measurement or statistical error (12%). After correcting for these errors, 53% had normal BMD, whereas only 26% retained the diagnosis of low BMD. The remaining 21% could not be given a definitive diagnosis. CONCLUSION: In children, the diagnosis of osteoporosis is often due to misinterpretation of a DEXA scan.
The National Children's Study (NCS) is a federally-sponsored, longitudinal study of environmental influences on the health and development of children across the United States (). Current plans are to study approximately 100,000 children and their families beginning before birth up to age 21 years. To explore potential biomarkers that could be important measurements in the NCS, we compiled the relevant scientific literature to identify both routine or standardized biological markers as well as new and emerging biological markers. Although the search criteria encouraged examination of factors that influence the breadth of child health and development, attention was primarily focused on exposure, susceptibility, and outcome biomarkers associated with four important child health outcomes: autism and neurobehavioral disorders, injury, cancer, and asthma. The Biomarkers Database was designed to allow users to: (1) search the biomarker records compiled by type of marker (susceptibility, exposure or effect), sampling media (e.g., blood, urine, etc.), and specific marker name; (2) search the citations file; and (3) read the abstract evaluations relative to our search criteria. A searchable, user-friendly database of over 2000 articles was created and is publicly available at: . PubMed was the primary source of references with some additional searches of Toxline, NTIS, and other reference databases. Our initial focus was on review articles, beginning as early as 1996, supplemented with searches of the recent primary research literature from 2001 to 2003. We anticipate this database will have applicability for the NCS as well as other studies of children's environmental health.
In the past, exercises aiming at an assessment of data uncertainty in environmental analysis were usually restricted to the analysis step, while sampling and pre-analytical sample treatment was largely ignored. Collaborative studies on the quantification of sampling errors require, besides a suitable and well characterized test site, the availability of a reference laboratory for the analysis of all of the samples taken in the context of the study by all participants and also test methods which do not contribute large and variable uncertainties due to long and complex analytical methodologies. Here we summarize the major analytical aspects of a European project on the identification and quantification of sampling influences on the determination of lead, cadmium, copper and zinc in soil. The participant group included the leading soil analysis laboratories in Europe; the test site at Dornach (CH) was well suited for the purpose and showed high metal gradients and differentiated land use. The analytical methods (wavelength-dispersive X-ray fluorescence spectrometry and solid-state Zeeman AAS) used in the study showed stable performance characteristics within the confidence interval of the certified reference materials used for the measurement quality control over the entire project period. Additionally, double-blind tests on split samples showed agreement of data in very narrow limits thus demonstrating the reliability of the reference database.
Assessment of BMD has become the essential part of evaluation of patients at risk of osteoporosis. It is likely that different BMD technologies will coexist in clinical practice in the future depending on varying clinical needs. DXA is currently the leading bone density technique because it has the capacity to measure axial and appendicular sites, superior monitoring capabilities, and more sophisticated reference databases and quality control procedures. More rapid and portable peripheral devices, such as peripheral DXA, peripheral instantaneous x-ray imager, and QUS, will likely be used for screening. This large variety of available bone densitometry techniques will provide a wide selection for clinicians to choose from. It may also add confusion, however, about which devices should be used and how to interpret data from different techniques. It is critical for clinicians to have a basic understanding of the technology being used, and the clinical advantages and disadvantages of each instrument, to choose properly which test to perform and interpret the obtained results. When combined with other major risks for fracture, such as age and prior fragility fractures, knowledge of the BMD is an invaluable tool in the assessment of patients with known or suspected osteoporosis.
A 9-locus microsatellite framework (minimal haplotype), previously developed for forensic purposes so as to facilitate stain analysis, personal identification and kinship testing, has been adopted for the establishment of a large reference database of male European Y-chromosomal haplotypes. The extent of population stratification pertaining to this database, an issue crucial for its practical forensic application, was assessed through analysis of molecular variance (AMOVA) of the 20 regional samples included. Despite the notion of some significant haplotype frequency differences, which were found to correlate with known demographic and historic features of Europeans, AMOVA generally revealed a high level of genetic homogeneity among the populations analyzed. Owing to their high diversity, however, accurate frequency estimation is difficult for Y-STR haplotypes when realistic (i.e. moderately sized) datasets are being used. As expected, strong pair-wise and higher order allelic associations were found to exist between all markers studied, implying that haplotype frequencies cannot be estimated as products of allele frequencies. A new extrapolation method was therefore developed which treats haplotype frequencies as random variables and generates estimates of the underlying distribution functions on the basis of closely related haplotypes. This approach, termed frequency 'surveying', is based upon standard population genetics theory and can in principle be applied to any combination of markers located on the Y-chromosome or in the mitochondrial genome. Application of the method to the quality assured reference Y-STR haplotype database described herein will prove very useful for the evaluation of positive trace-donor matches in forensic casework.
This paper presents a simple methodology for combining bone densitometry data from different sites in the UK, having instruments from the same manufacturer (LUNAR Radiation). Additive normalization factors were used on all data prior to inclusion in a reference database which ultimately included data on 1372 Caucasian women, aged 20-70 years, of whom 749 were post-menopausal. Reference data for spine (L2-L4) and femoral neck bone mineral density are given in tabular form as 3 year moving averages for: (1) all women; (2) perimenopausal women grouped by menopausal status; and (3) post-menopausal women with respect to years since menopause. These data may be used to construct Z-score. T-score or percentile reporting ranges and may be adopted as the core for a UK reference range.
AraCyc is a database containing biochemical pathways of Arabidopsis, developed at The Arabidopsis Information Resource (http://www.arabidopsis.org). The aim of AraCyc is to represent Arabidopsis metabolism as completely as possible with a user-friendly Web-based interface. It presently features more than 170 pathways that include information on compounds, intermediates, cofactors, reactions, genes, proteins, and protein subcellular locations. The database uses Pathway Tools software, which allows the users to visualize a bird's eye view of all pathways in the database down to the individual chemical structures of the compounds. The database was built using Pathway Tools' Pathologic module with MetaCyc, a collection of pathways from more than 150 species, as a reference database. This initial build was manually refined and annotated. More than 20 plant-specific pathways, including carotenoid, brassinosteroid, and gibberellin biosyntheses have been added from the literature. A list of more than 40 plant pathways will be added in the coming months. The quality of the initial, automatic build of the database was compared with the manually improved version, and with EcoCyc, an Escherichia coli database using the same software system that has been manually annotated for many years. In addition, a Perl interface, PerlCyc, was developed that allows programmers to access Pathway Tools databases from the popular Perl language. AraCyc is available at the tools section of The Arabidopsis Information Resource Web site (http://www.arabidopsis.org/tools/aracyc).
An ambulatory-care patient-tracking system has been implemented that records non-categorical problem descriptions in the outpatient problem list. The system does not restrict physicians to the use of predefined diagnostic categories. Instead, the system stores patient problems in a database as free-text records. Subsequent diagnostic categorization and coding is accomplished through prompted free-text input and appropriate reference databases. This system design allows an outpatient problem-list summary to reflect non-categorical health-status information in addition to coded medical diagnoses.
OBJECTIVE: To compare the accuracy of dermatologists and primary care physicians (PCPs) in identifying pigmented lesions suggestive of melanoma and making the appropriate management decision to perform a biopsy or to refer the patient to a specialist. DATA SOURCES: Studies published between January 1966 and October 1999 in the MEDLINE, EMBASE, and CancerLit databases; reference lists of identified studies; abstracts from recent conference proceedings; and direct contact with investigators. Medical subject headings included melanoma, diagnosis, screening, primary care, family practitioner, general practitioner, internal medicine, dermatologist, and skin specialist. Articles were restricted to those involving human subjects. STUDY SELECTION: Studies that presented sufficient data to determine the sensitivity and specificity of dermatologists' or PCPs' ability to correctly diagnose lesions suggestive of melanoma and to perform biopsies on or refer patients with such lesions. DATA EXTRACTION: Two reviewers independently abstracted data regarding the sensitivity and specificity of the dermatologists and PCPs for diagnostic and biopsy or referral accuracy. Disagreements were resolved by discussion. The quality of the studies was also evaluated. DATA SYNTHESIS: Thirty-two studies met inclusion criteria; 10 were prospective studies. For diagnostic accuracy, sensitivity was 0.81 to 1.00 for dermatologists and 0.42 to 1.00 for PCPs. None of the studies reported specificity for dermatologists; one reported specificity for PCPs (0.98). For biopsy or referral accuracy, sensitivity ranged from 0.82 to 1.00 for dermatologists and 0.70 to 0.88 for PCPs; specificity, 0.70 to 0.89 for dermatologists and 0.70 to 0.87 for PCPs. Receiver operating characteristic curves for biopsy or referral ability were inconclusive. CONCLUSIONS: The published data are inadequate to demonstrate differences in dermatologists' and PCPs' diagnostic and biopsy or referral accuracy of lesions suggestive of melanoma. We offer study design suggestions for future studies.
This case study examined the recent withdrawal of valdecoxib to determine the timeliness of updates in commonly used information sources used by healthcare professionals. The method included assembling a purposive sample of 15 drug reference and warning systems that were then systematically monitored for several months after the withdrawal of valdecoxib to determine the time to update this information. These information sources were classified and described qualitatively. A time to diffusion curve was plotted and the average number of days to report the drug withdrawal or update reference databases was calculated. Only 2 of 15 information systems reported the drug withdrawal on the actual date of the FDA announcement. Institutional electronic textbooks took an average of 109.8 days (+/-14 days) to report the withdrawal. In addition, one pharma-sponsored dissemination source (Peerview Press) had not updated their information as of this publication.
Caves represent a unique environment in which to study subsurface geomicrobial interactions and processes. One of the primary techniques used to study such geologic samples is molecular phylogenetic analysis, but this technique is hampered by low microbial biomass and calcium in the host rock, often leading to poor and irreproducible DNA extraction. We describe an improved protocol to recover extremely low amounts of DNA from calcium-rich geologic samples. This protocol relies on the use of the synthetic DNA molecule poly-dIdC, to act both as blocking agent and carrier molecule to increase the yield of DNA, and dialysis to remove calcium inhibitors of PCR amplification. Further, we demonstrate that many traditionally used laboratory substrates contain microbial DNA that can be amplified through the polymerase chain reaction (PCR) and contaminate molecular phylogenetic profiles. While the number of potential contaminants can be minimized, it cannot be eliminated from extraction techniques. We have therefore established the low-biomass contaminant (LBC) database, which contains the 16S rRNA gene sequences of species that have been identified as common laboratory contaminants. These identified contaminants provide a reference database to allow investigators to critically evaluate certain species identified within their phylogenetic profile when examining such low-biomass environments.
BACKGROUND: We present a biological data warehouse called Atlas that locally stores and integrates biological sequences, molecular interactions, homology information, functional annotations of genes, and biological ontologies. The goal of the system is to provide data, as well as a software infrastructure for bioinformatics research and development. DESCRIPTION: The Atlas system is based on relational data models that we developed for each of the source data types. Data stored within these relational models are managed through Structured Query Language (SQL) calls that are implemented in a set of Application Programming Interfaces (APIs). The APIs include three languages: C++, Java, and Perl. The methods in these API libraries are used to construct a set of loader applications, which parse and load the source datasets into the Atlas database, and a set of toolbox applications which facilitate data retrieval. Atlas stores and integrates local instances of GenBank, RefSeq, UniProt, Human Protein Reference Database (HPRD), Biomolecular Interaction Network Database (BIND), Database of Interacting Proteins (DIP), Molecular Interactions Database (MINT), IntAct, NCBI Taxonomy, Gene Ontology (GO), Online Mendelian Inheritance in Man (OMIM), LocusLink, Entrez Gene and HomoloGene. The retrieval APIs and toolbox applications are critical components that offer end-users flexible, easy, integrated access to this data. We present use cases that use Atlas to integrate these sources for genome annotation, inference of molecular interactions across species, and gene-disease associations. CONCLUSION: The Atlas biological data warehouse serves as data infrastructure for bioinformatics research and development. It forms the backbone of the research activities in our laboratory and facilitates the integration of disparate, heterogeneous biological sources of data enabling new scientific inferences. Atlas achieves integration of diverse data sets at two levels. First, Atlas stores data of similar types using common data models, enforcing the relationships between data types. Second, integration is achieved through a combination of APIs, ontology, and tools. The Atlas software is freely available under the GNU General Public License at: http://bioinformatics.ubc.ca/atlas/
The IMB Jena Image Library of Biological Macromolecules (http://www.imb-jena.de/IMAGE.html) is aimed at a better dissemination of information on three-dimensional biopolymer structures with an emphasis on visualization and analysis. It provides access to all structure entries deposited at the Protein Data Bank (PDB) and Nucleic Acid Database (NDB). In addition, basic information on the architecture of biological macromolecules is offered. Recent developments include a site database and an analysis tool that identifies all residues surrounding hetero components or sites according to geometrical criteria. This enables one to search for all structures with a certain pattern of amino acids/nucleotides/water adjacent to hetero components or sites. A new PDB/SWISS-PROT cross-reference database combines information from both PDB and SWISS-PROT, thus providing significantly more cross-references than either PDB or SWISS-PROT. The existing brief descriptions of X-ray, NMR and FTIR methods for structure determination are supplemented by information on circular dichroism.
The field of proteomics involves the combined application of advanced separation techniques, mass spectrometry, and bioinformatics tools to characterize proteins in complex biological mixtures. Here we report the identification of nine proteins from the human pituitary proteome, using the proteomics approach. The pituitary proteins were separated by two-dimensional electrophoresis, and were visualized by silver staining. The proteins of interest were subjected to in-gel digestion with trypsin, and the masses of the resulting peptides were determined by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. This tryptic mass map was used to identify the proteins through a search of a protein-sequence database. The identified proteins include important hormones, and enzymes with various catalytic activities. These proteins will be used to construct a two-dimensional reference database of the human pituitary. This database will be employed to study changes in the pituitary proteome that are associated with the formation of pituitary tumors.
BACKGROUND: Repbase is a reference database of eukaryotic repetitive DNA, which includes prototypic sequences of repeats and basic information described in annotations. Updating and maintenance of the database requires specialized tools, which we have created and made available for use with Repbase, and which may be useful as a template for other curated databases. RESULTS: We describe the software tools RepbaseSubmitter and Censor, which are designed to facilitate updating and screening the content of Repbase. RepbaseSubmitter is a java-based interface for formatting and annotating Repbase entries. It eliminates many common formatting errors, and automates actions such as calculation of sequence lengths and composition, thus facilitating curation of Repbase sequences. In addition, it has several features for predicting protein coding regions in sequences; searching and including Pubmed references in Repbase entries; and searching the NCBI taxonomy database for correct inclusion of species information and taxonomic position. Censor is a tool to rapidly identify repetitive elements by comparison to known repeats. It uses WU-BLAST for speed and sensitivity, and can conduct DNA-DNA, DNA-protein, or translated DNA-translated DNA searches of genomic sequence. Defragmented output includes a map of repeats present in the query sequence, with the options to report masked query sequence(s), repeat sequences found in the query, and alignments. CONCLUSION: Censor and RepbaseSubmitter are available as both web-based services and downloadable versions. They can be found at http://www.girinst.org/repbase/submission.html (RepbaseSubmitter) and http://www.girinst.org/censor/index.php (Censor).