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As chins gain favor and efficiency in several regions of the country, they are increasingly used to speed both financial and clinical data interchanges. Technologic advances in information management are shifting the laboratory from a passive entity generating data to an active medical support service.
The most basic conclusion coming out of the EDUCOM seminars is that computer networking must be acknowledged as an important new mode for obtaining information and computation (15). It is a real alternative that needs to be given serious attention in current planning and decision-making. Yet the fact is that many institutions are not taking account of networks when they confer on whether or how to replace their main computer. Articulation of the possibilities of computer networks goes back to the early 1960's and before, and working networks have been in evidence for several years now, both commercially and in universities. What is new, however, is the unmistakable recognition-bordering on a sense of the inevitable-that networks are finally practical and here to stay. The visionary and promotional phases of computer networks are over. It is time for hard-nosed comparative analysis (16). Another conclusion of the seminars has to do with the factors that hinder the fuller development of networking. The major problems to be overcome in applying networks to research and education are political, organizational, and economic in nature rather than technological. This is not to say that the hardware and software problems of linking computers and information systems are completely solved, but they are not the big bottlenecks at present. Research and educational institutions must find ways to organize themselves as well as their computers to work together for greater resource sharing. The coming of age of networks takes on special significance as a result of widespread dissatisfactions expressed with the present computing situation. There is a feeling that the current mode of autonomous, self-sufficient operation in the provision of computing and information services is frequently wasteful, deficient, and unresponsive to users' needs because of duplication of effort from one installation to another, incompatibilities, and inadequate documentation, program support, and user assistance. Complaints about the relative lack of uniform standards and the paucity of information on what programs and data are available and how to get and use them are commonplace. The human tendency, when beset by problems such as these, is to seek a savior in the next new technology-networks in this case. But networking does not in and of itself offer a solution to current deficiencies. What it does offer is a promising vehicle with which to bring about important changes in user practices, institutional procedures, and government policy that can lead to effective solutions. Thus more critical than whether networking is developed and applied is how it is developed and applied. For example, networking emphasizes the need for standards and good documentation. Unless effective mechanisms are developed and strong measures taken in networking to ensure that suitable standards and documentation are developed, present inadequacies could get worse, not better.
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A major challenge in human genetics is identifying the molecular basis of common heritable disorders. In contrast to rare single-gene diseases, multifactorial disorders are thought to arise from the combined effect of multiple gene variants, such that any single variant may have only a modest effect on disease susceptibility. We present a method to identify genes that may harbor a significant proportion of the genetic variation that predisposes individuals to a given multifactorial disorder. First, we perform an automated literature analysis that predicts physical interactions (edges) among candidate disease genes (seed nodes, selected on the basis of prior information) and other molecular entities. We derive models of molecular networks from this analysis and map the seed nodes to them. We then compute the graph-theoretic distance (the minimum number of edges that must be traversed) between the seed nodes and all other nodes in the network. We assume that nodes that are found in close proximity to multiple seed nodes are the best disease-related candidate genes. To evaluate this approach, we selected four seed genes, each with a proven role in Alzheimer's disease (AD). The method performed well in predicting additional network nodes that match AD gene candidates identified manually by an expert. We also show that the method prioritizes among the seed nodes themselves, rejecting false-positive seeds that are derived from (noisy) whole-genome genetic-linkage scans. We propose that this strategy will provide a valuable means to bridge genetic and genomic knowledge in the search for genetic determinants of multifactorial disorders.
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Because the health care administrator faces unprecedented demands concerning information, well-designed and carefully selected information systems have become a critical factor in the viability and survival of health care institutions. Local area network systems are having a significant impact in this regard. Among their advantages are flexibility, dependability, low cost, and modularity. Health care facilities, have found networking to be a simple, cost-effective solution to collecting, processing, and distributing large volumes of data. The keys to a successful implementation recommended in this article should assist health care professionals once they have made the hard decision to use a local area network to process their day-to-day transactions.
BACKGROUND: To elucidate networks of Mycobacterium tuberculosis transmission, it may be appropriate to characterize the types of relationships among tuberculosis (TB) cases and their contacts (with and without latent TB infection) in addition to relying on traditional efforts to distinguish 'close' from 'casual' contacts. SETTING: A TB outbreak in a US low incidence state. OBJECTIVE: To evaluate whether social network analysis can provide insights into transmission settings that might otherwise go unrecognized by routine practices. DESIGN: All adult outbreak-associated cases (n = 19) and a convenience sample of their contacts with and without latent TB infection (LTBI) (n = 26) were re-interviewed in 2001 using a structured questionnaire. Network analysis software was used to create diagrams illustrating important persons within the outbreak network, as well as types of activities TB cases engaged in with their contacts. RESULTS: Drug use and drug sharing were more commonly reported among cases and their infected contacts than among contacts without LTBI. TB cases central to the outbreak network used crack cocaine, uncovering the need to focus control efforts on specific sites and persons involved in illicit drug use. CONCLUSION: Outbreaks occur even in areas with low TB incidence, frequently among groups whose drug use or other illegal activities complicate control efforts. TB programs should consider the use of network analysis as a supplement to routine contact investigations to identify unrecognized patterns of M. tuberculosis transmission.
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Novel high-throughput measurement techniques in vivo are beginning to produce dense high-quality time series which can be used to investigate the structure and regulation of biochemical networks. We propose an automated information extraction procedure which takes advantage of the unique S-system structure and supports model building from time traces, curve fitting, model selection, and structure identification based on parameter estimation. The procedure comprises of three modules: model Generation, parameter estimation or model Fitting, and model Selection (GFS algorithm). The GFS algorithm has been implemented in MATLAB and returns a list of candidate S-systems which adequately explain the data and guides the search to the most plausible model for the time series under study. By combining two strategies (namely decoupling and limiting connectivity) with methods of data smoothing, the proposed algorithm is scalable up to realistic situations of moderate size. We illustrate the proposed methodology with a didactic example.