Evaluation of web accessibility of consumer health information websites.
The objectives of the study are to construct a comprehensive framework for web accessibility evaluation, to evaluate the current status of web accessibility of consumer health information websites and to investigate the relationship between web accessibility and property of the websites. We selected 108 consumer health information websites from the directory service of a Web search engine. We used Web accessibility specifications to construct a framework for the measurement of Web Accessibility Barriers (WAB) of website. We found that none of the websites is completely accessible to people with disabilities, but governmental and educational health information websites exhibit better performance on web accessibility than other categories of websites. We also found that the correlation between the WAB score and the popularity of a website is statistically significant. (+info)
Depth of proteome issues: a yeast isotope-coded affinity tag reagent study.
As a test case for optimizing how to perform proteomics experiments, we chose a yeast model system in which the UPF1 gene, a protein involved in nonsense-mediated mRNA decay, was knocked out by homologous recombination. The results from five complete isotope-coded affinity tag (ICAT) experiments were combined, two using matrix-assisted laser desorption/ionization (MALDI) tandem mass spectrometry (MS/MS) and three using electrospray MS/MS. We sought to assess the reproducibility of peptide identification and to develop an informatics structure that characterizes the identification process as well as possible, especially with regard to tenuous identifications. The cleavable form of the ICAT reagent system was used for quantification. Most proteins did not change significantly in expression as a consequence of the upf1 knockout. As expected, the Upf1 protein itself was down-regulated, and there were reproducible increases in expression of proteins involved in arginine biosynthesis. Initially, it seemed that about 10% of the proteins had changed in expression level, but after more thorough examination of the data it turned out that most of these apparent changes could be explained by artifacts of quantification caused by overlapping heavy/light pairs. About 700 proteins altogether were identified with high confidence and quantified. Many peptides with chemical modifications were identified, as well as peptides with noncanonical tryptic termini. Nearly all of these modified peptides corresponded to the most abundant yeast proteins, and some would otherwise have been attributed to "single hit" proteins at low confidence. To improve our confidence in the identifications, in MALDI experiments, the parent masses for the peptides were calibrated against nearby components. In addition, five novel parameters reflecting different aspects of identification were collected for each spectrum in addition to the Mascot score that was originally used. The interrelationship between these scoring parameters and confidence in protein identification is discussed. (+info)
Bridging the digital divide: reaching vulnerable populations.
The AMIA 2003 Spring Congress entitled "Bridging the Digital Divide: Informatics and Vulnerable Populations" convened 178 experts including medical informaticians, health care professionals, government leaders, policy makers, researchers, health care industry leaders, consumer advocates, and others specializing in health care provision to underserved populations. The primary objective of this working congress was to develop a framework for a national agenda in information and communication technology to enhance the health and health care of underserved populations. Discussions during four tracks addressed issues and trends in information and communication technologies for underserved populations, strategies learned from successful programs, evaluation methodologies for measuring the impact of informatics, and dissemination of information for replication of successful programs. Each track addressed current status, ideal state, barriers, strategies, and recommendations. Recommendations of the breakout sessions were summarized under the overarching themes of Policy, Funding, Research, and Education and Training. The general recommendations emphasized four key themes: revision in payment and reimbursement policies, integration of health care standards, partnerships as the key to success, and broad dissemination of findings including specific feedback to target populations and other key stakeholders. (+info)
Tackling publication bias and selective reporting in health informatics research: register your eHealth trials in the International eHealth Studies Registry.
Beginning in July 2005, several major medical journals, including the Journal of Medical Internet Research, will only consider trials for publication that have been registered in a trial registry before they started. This is to reduce publication bias and to prevent selective reporting of positive outcomes. As existing clinical trial registers seem to be unsuitable or suboptimal for eHealth studies, a free International eHealth Study Registry (IESR) has been set up, allowing registration of trials (including non-randomized studies) in the field of health informatics and assigning an International eHealth Study Number (IESN). The IESR should meet the requirements of journal editors for a-priori registration of a study. We hope IESR will become the preferred choice for registration of eHealth studies and, as an secondary benefit, will become an international repository of ongoing eHealth projects, thereby enhancing global collaboration and reducing duplication of effort. (+info)
Development of an integrated genome informatics, data management and workflow infrastructure: a toolbox for the study of complex disease genetics.
The genetic dissection of complex disease remains a significant challenge. Sample-tracking and the recording, processing and storage of high-throughput laboratory data with public domain data, require integration of databases, genome informatics and genetic analyses in an easily updated and scaleable format. To find genes involved in multifactorial diseases such as type 1 diabetes (T1D), chromosome regions are defined based on functional candidate gene content, linkage information from humans and animal model mapping information. For each region, genomic information is extracted from Ensembl, converted and loaded into ACeDB for manual gene annotation. Homology information is examined using ACeDB tools and the gene structure verified. Manually curated genes are extracted from ACeDB and read into the feature database, which holds relevant local genomic feature data and an audit trail of laboratory investigations. Public domain information, manually curated genes, polymorphisms, primers, linkage and association analyses, with links to our genotyping database, are shown in Gbrowse. This system scales to include genetic, statistical, quality control (QC) and biological data such as expression analyses of RNA or protein, all linked from a genomics integrative display. Our system is applicable to any genetic study of complex disease, of either large or small scale. (+info)
Global Infectious Diseases and Epidemiology Network (GIDEON): a world wide Web-based program for diagnosis and informatics in infectious diseases.
The Global Infectious Diseases and Epidemiology Network (GIDEON) (http://www.gideononline.com) consists of 4 modules. The first is designed to generate a ranked differential diagnosis list for any infectious diseases scenario in any of 220 countries. The second follows the country-specific epidemiology of 337 individual diseases. The third presents a comprehensive encyclopedia of 308 generic anti-infective drugs and vaccines, including a listing of >9500 trade names. The fourth generates a ranked identification list based on the phenotype of bacteria, mycobacteria, and yeasts. The program performs well and serves as a useful paradigm for World Wide Web-based informatics. GIDEON is an eclectic program that can serve the needs of clinicians, epidemiologists, and microbiologists working in the fields of infectious diseases and geographic medicine. (+info)
Metabolite profiling of fungi and yeast: from phenotype to metabolome by MS and informatics.
Filamentous fungi and yeast from the genera Saccharomyces, Penicillium, Aspergillus, and Fusarium are well known for their impact on our life as pathogens, involved in food spoilage by degradation or toxin contamination, and also for their wide use in biotechnology for the production of beverages, chemicals, pharmaceuticals, and enzymes. The genomes of these eukaryotic micro-organisms range from about 6000 genes in yeasts (S. cerevisiae) to more than 10,000 genes in filamentous fungi (Aspergillus sp.). Yeast and filamentous fungi are expected to share much of their primary metabolism; therefore much understanding of the central metabolism and regulation in less-studied filamentous fungi can be learned from comparative metabolite profiling and metabolomics of yeast and filamentous fungi. Filamentous fungi also have a very active and diverse secondary metabolism in which many of the additional genes present in fungi, compared with yeast, are likely to be involved. Although the 'blueprint' of a given organism is represented by the genome, its behaviour is expressed as its phenotype, i.e. growth characteristics, cell differentiation, response to the environment, the production of secondary metabolites and enzymes. Therefore the profile of (secondary) metabolites--fungal chemodiversity--is important for functional genomics and in the search for new compounds that may serve as biotechnology products. Fungal chemodiversity is, however, equally efficient for identification and classification of fungi, and hence a powerful tool in fungal taxonomy. In this paper, the use of metabolite profiling is discussed for the identification and classification of yeasts and filamentous fungi, functional analysis or discovery by integration of high performance analytical methodology, efficient data handling techniques and core concepts of species, and intelligent screening. One very efficient approach is direct infusion Mass Spectrometry (diMS) integrated with automated data handling, but a full metabolic picture requires the combination of several different analytical techniques. (+info)
Gene Ontology: looking backwards and forwards.
The Gene Ontology consortium began six years ago with a group of scientists who decided to connect our data by sharing the same language for describing it. Its most significant achievement lies in uniting many independent biological database efforts into a cooperative force. (+info)