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At least 127 records · Page 7Linked to original sources
PubMed2003

Random Boolean network models and the yeast transcriptional network.

The recently measured yeast transcriptional network is analyzed in terms of simplified Boolean network models, with the aim of determining feasible rule structures, given the requirement of stable solutions of the generated Boolean networks. We find that, for ensembles of generated models, those with canalyzing Boolean rules are remarkably stable, whereas those with random Boolean rules are only marginally stable. Furthermore, substantial parts of the generated networks are frozen, in the sense that they reach the same state, regardless of initial state. Thus, our ensemble approach suggests that the yeast network shows highly ordered dynamics.

Computational Biology↗
PubMed1991

Designing a neural network simulator--the MENS modelling environment for network systems: II.

During recent years, neural network research has been extended to a large number of different fields, increasingly attracting the interest of workers from various disciplines. The computer simulations carried out with this research require an appropriate software environment. The computational similarities of many kinds of simulations allow the design of software components that are largely independent of the specific application. These considerations are reflected, for example, by the general layout of the MENS network simulator, as described in the accompanying first paper. This paper presents the design considerations for the simulator's different software components in more detail. In particular, design and implementation are discussed with respect to computational and memory efficiency. The discussion includes, for example, the representation of a network by the simulator's data structure, the file-driven configuration and initialization of a network, the simulator's stimulus and monitor system, and the simulator's control structures. In addition, the separation and interaction of application-specific and application-independent software components are addressed. Particular performance aspects comprise the implementation of synaptic delays, the dynamic deletion of synaptic links in network learning, and the preprocessing of stimulus films. In addition, some general aspects of simulator performance and testing are considered. The material presented in this paper concerns both the development of new simulation software and the efficient use of existing programs. Therefore, both the general user as well as the software designer may hopefully benefit from this presentation.

Animals↗
PubMed2006

A gradual noisy chaotic neural network for solving the broadcast scheduling problem in packet radio networks.

In this paper, we propose a gradual noisy chaotic neural network (G-NCNN) to solve the NP-complete broadcast scheduling problem (BSP) in packet radio networks. The objective of the BSP is to design an optimal time-division multiple-access (TDMA) frame structure with minimal TDMA frame length and maximal channel utilization. A two-phase optimization is adopted to achieve the two objectives with two different energy functions, so that the G-NCNN not only finds the minimum TDMA frame length but also maximizes the total node transmissions. In the first phase, we propose a G-NCNN which combines the noisy chaotic neural network (NCNN) and the gradual expansion scheme to find a minimal TDMA frame length. In the second phase, the NCNN is used to find maximal node transmissions in the TDMA frame obtained in the first phase. The performance is evaluated through several benchmark examples and 600 randomly generated instances. The results show that the G-NCNN outperforms previous approaches, such as mean field annealing, a hybrid Hopfield network-genetic algorithm, the sequential vertex coloring algorithm, and the gradual neural network.

Electricity↗
PubMed1992

The use of wide area computer networks in disaster management and the implications for hospital/medical networks.

Computer-mediated communication in various forms is already being used in all phases of disaster management--preparation, response, recovery, and long-term mitigation. However, to date wide area computer networks--particularly the Internet (the supernetwork of networks)--have been used only to a limited extent in disaster management and prevention. Some of these applications are described in this paper. Nevertheless, the high speed and ease of information transfer by computer network and the vast resources becoming available on the Internet make it inevitable that the use of computer networks to temper disasters will increase enormously in the next decade. The Internet will provide a key means through which networks initially dedicated to solely medical purposes and the individuals who use them will become involved not only in disaster response and mitigation worldwide, but in the global community and consciousness that is the Internet.

Australia↗
PubMedDate not supplied

A neural network approach to approximating MAP in belief networks.

Bayesian belief networks (BBN) are a widely studied graphical model for representing uncertainty and probabilistic interdependence among variables. One of the factors that restricts the model's wide acceptance in practical applications is that the general inference with BBN is NP-hard. This is also true for the maximum a posteriori probability (MAP) problem, which is to find the most probable joint value assignment to all uninstantiated variables, given instantiation of some variables in a BBN. To circumvent the difficulty caused by MAP's computational complexity, we suggest in this paper a neural network approximation approach. With this approach, a BBN is treated as a neural network without any change or transformation of the network structure, and the node activation functions are derived based on an energy function defined over a given BBN. Three methods are developed. They are the hill-climbing style discrete method, the simulated annealing method, and the continuous method based on the mean field theory. All three methods are for BBN of general structures, with the restriction that nodes of BBN are binary variables. In addition, rules for applying these methods to noisy-or networks are also developed, which may lead to more efficient computation in some cases. These methods' convergence is analyzed, and their validity tested through a series of computer experiments with two BBN of moderate size and complexity. Although additional theoretical and empirical work is needed, the analysis and experiments suggest that this approach may lead to effective and accurate approximation for MAP problems.

Algorithms↗
PubMed1996

Using neural networks to solve the multicast routing problem in packet radio networks.

The primary function of a packet radio network is the efficient transfer of information between source and destination nodes using minimal bandwidth and end-to-end delay. Many researchers have investigated the problem of minimizing the end-to-end delay from a single source to a single destination for a variety of networks; however, very little work is reported about routing mechanisms for the common case where a particular information packet is intended to be sent to more than one destination in the network. This is known as multicasting. A simplified version of the problem is to ignore the packet delay at each node, then the problem becomes one of finding solutions which require the least number of transmissions. Determination of an optimal solution is NP-complete meaning that suboptimal solutions are frequently tolerated. The problem becomes more rigorous if packet delays are included in the network topology. This paper describes a practical technique for the computation of optimum or near optimum solutions to the multicasting problem with and without packet delay. The method is based on the Hopfield neural network and experiment has shown this method to yield near optimal solutions while requiring a minimum of CPU time.

Algorithms↗
PubMed1998

On the use of neural network techniques to analyze sleep EEG data. Third communication: robustification of the classificator by applying an algorithm obtained from 9 different networks.

This is the third communication on the use of neural network techniques to classify sleep stages. In our first communication we presented the algorithms and the selection of the feature space and its reduction by using evolutionary and genetic procedures. In our second communication we trained the evolutionary optimized networks on the basis of multiple subject data in context with some smoothing algorithms in analogy of Rechtschaffen and Kales (RK). In this third communication we could demonstrate that the robustness concerning individual specific features of automatically generated sleep profiles could be reasonably improved by an additional modification of the procedure used by SASCIA (Sleep Analysis System to Challenge Innovative Artificial Networks). The outputs of nine different networks that were created by the data of 9 different subjects were used simultaneously for classification. The medians of the values obtained in each output measure were selected for the allocation to a sleep stage. The fitness criteria of 16 automatically generated sleep profiles showed reasonable concordance with the expert profile. Even though in single cases the concordance between conventional RK classifications and automatically generated profiles were a few percentages lower, the average correct classification of the 12 classified subjects improved substantially, thus proving that the classifier is more robust against individuum-specific variability. Despite the fact that the expert generally employs three channels (EEG, EMG and EOG), at least to build up sleep profiles, the SASCIA system was able to produce profiles on the basis of only one EEG channel with 80% concordance and a correlation coefficient of 0.86. The feature selections were performed by genetic algorithms and the topologies of the networks were optimized by evolutionary algorithms. This algorithm will now be used for larger sample forward classification.

Algorithms↗
PubMedDate not supplied

Practice patterns of family physicians in practice-based research networks: a report from ASPN. Ambulatory Sentinel Pratice Network.

BACKGROUND: Practice-based research networks are growing and undertaking larger and more complex studies to inform the clinical practice of family physicians. We describe a study that compares clinical behaviors of physicians in the Ambulatory Sentinel Practice Network (ASPN), a large national practice-based research network, with those from the National Ambulatory Medical Care Survey (NAMCS). METHODS: A survey, replicating NAMCS, was conducted among 129 family physician members of ASPN. Nested logistic regression was used to determine which services could predict ASPN membership after adjustment for common and easily observed patient and physician characteristics. RESULTS: Of 20 specific patient services, only 4 were predictive of membership in ASPN. Of these 4, 2 were screening or diagnostic services; ASPN physicians were 1.18 times more likely to obtain a blood pressure measurement and 0.60 times as likely to order a culture for streptococcal pharyngitis. ASPN physicians were 2.30 times more likely to provide family planning counseling and 1.66 times more likely to provide smoking cessation counseling after adjusting for patient smoking status. CONCLUSIONS: We conclude that there are minimal differences in the practice patterns of family physicians participating in a large national practice-based research network and those included in the probability sample of NAMCS. Additional work is needed to examine further those characteristics of the phenomena observed in practice-based research network research that might affect generalizability of results to the larger community of practicing family physicians.

Community Networks↗
PubMed1999

An electronic network for the surveillance of antimicrobial resistance in bacterial nosocomial isolates in Greece. The Greek Network for the Surveillance of Antimicrobial Resistance.

The present article reports an evaluation of the national electronic network for the continuous monitoring of antimicrobial resistance in Greece. The network employs a common electronic code and data format and uses WHONET software. Our four years' experience with the network confirms its practicality. A total of 22 hospitals in Greece are currently using the software, of which 19 participate in the network. Analysis of the information obtained has greatly helped in identifying the main factors responsible for the emergence of antimicrobial resistance in the participating hospitals. The data collected have also helped to identify priorities for further investigation of the genetic and molecular mechanisms responsible for the emergence of resistance and facilitated development of hospital-based empirical therapy of infections. In conclusion, the implementation of national networks for the surveillance of antimicrobial resistance should be regarded as a priority.

Computer Communication Networks↗
PubMed1995

[Sentinel networks. The national public health network. State information].

In the area of health, the information system used by the authorities is based on a series of networks that need to be coordinated. 1. State information: State information as regards health epidemiology was for a long time fragmented. The reasons for this relative ignorance are varied, and are based both on professional and technical factors (preference of physicians for personal exchange rather than for statistical analysis, difficulties in data collection and mathematical processing), and on socio-political factors (the euphoria of years of economic growth). For a long time only the causes of death were appropriately documented (cf. Mme Facy's report). In the last decade, a variety of initiatives has been directed towards all fields, and morbidity is becoming better defined thanks to the ORS (Regional Health Observatories) (cf. M. Garro's speech) and health registers (cf. M. Schaffer). Warning systems are becoming a principal preoccupation for most people in positions of authority, and explain the proliferation of surveillance networks. 2. Sentinel networks: A 'sentinel network' is an interactive surveillance system involving the collection of health data on a routine basis by a group of doctors (general physicians, biologists, etc.). Initially conceived for the surveillance of communicable diseases, they are also used for all diseases requiring early warning and rapid intervention (effects of sudden pollution, surveillance of drugs and poisons, etc.). These sentinel networks have expanded in our countries to complement the compulsory notification systems for infectious diseases, whose 'passive' nature often leads to under-notification (and therefore a non-representative selection) and delayed notification of cases, and whose range of influence does not cover all communicable diseases.(ABSTRACT TRUNCATED AT 250 WORDS)

Community Networks↗
PubMed1993

How representative of typical practice are practice-based research networks? A report from the Ambulatory Sentinel Practice Network Inc (ASPN)

OBJECTIVE: To evaluate the patients and practices of family physicians in a national practice-based research network to understand whether results from practice-based research networks are likely to be relevant to other practicing clinicians. STUDY DESIGN: Survey focused on family physicians that replicated the National Ambulatory Medical Care Survey (NAMCS). SETTING: The Ambulatory Sentinel Practice Network Inc (ASPN), a practice-based research network, consisting of volunteer primary care practices that serve approximately 350,000 patients. OUTCOME MEASURES: Comparison of visits reported in ASPN with the visits reported in the 1990 NAMCS in terms of patient demographics, reasons for visit, diagnostic and therapeutic services, diagnoses, disposition, and amount of time spent with patients. RESULTS: Overall, the two samples differed with respect to demographic characteristics of patients, while problems, diagnoses, services, disposition, and time spent with patients were similar. Specific pair-wise comparisons identified areas of difference. CONCLUSION: The ASPN and possibly other similar practice-based research networks are sufficiently representative of family practice to serve as useful laboratories in which family practice and primary care can be explored.

Adolescent↗
PubMed1985

Network therapy: an outcome study of twelve social networks.

Twelve social networks received a course of network therapy at the Mount Tom Institute in Holyoke, Massachusetts, by the Network Therapy Project. A total of twenty-five 3-hour meetings included 201 participants. A study was conducted examining the number and type of service contacts in the clients' central medical files three months prior to the completion of network therapy and at two 3-months intervals after therapy was terminated. Entries were made in clients' charts by case managers, by crisis team staff, and by other mental health professionals. An historical comparison group was studied by randomly choosing 12 clients from the 19 referred for network therapy who did not receive this treatment. The comparison group showed an overall 17% decrease in service utilization after the date of referral, compared to a 76% decrease postnetwork therapy in the treatment group. The difference between the group outcomes was statistically significant.

Community Mental Health Services↗
PubMed2002

Ingeneue: a versatile tool for reconstituting genetic networks, with examples from the segment polarity network.

Here we describe a software tool for synthesizing molecular genetic data into models of genetic networks. Our software program Ingeneue, written in Java, lets the user quickly turn a map of a genetic network into a dynamical model consisting of a set of ordinary differential equations. We developed Ingeneue as part of an ongoing effort to explore the design and evolvability of genetic networks. Ingeneue has three principal advantages over other available mathematical software: it automates instantiation of the same network model in each cell in a 2-D sheet of cells; it constructs model equations from pre-made building blocks corresponding to common biochemical processes; and it automates searches through parameter space, sensitivity analyses, and other common tasks. Here we discuss the structure of the software and some of the issues we have dealt with. We conclude with some examples of results we have achieved with Ingeneue for the Drosophila segment polarity network.

Animals↗
PubMed2006

Guideline-defining asthma clinical trials of the National Heart, Lung, and Blood Institute's Asthma Clinical Research Network and Childhood Asthma Research and Education Network.

Because of an increasing prevalence, morbidity, and mortality associated with asthma, the National Heart, Lung, and Blood Institute created the Asthma Clinical Research Network and the Childhood Asthma Research and Education Network to improve public health. The objectives of these clinical research networks are to conduct multiple, well-designed clinical trials for rapid evaluation of new and existing therapeutic approaches to asthma and to disseminate laboratory and clinical findings to the health care community. These trials comprise a large proportion of the data driving the treatment guidelines established and reviewed by the National Asthma Education and Prevention Program. This article will review the basic design and major findings of selected Asthma Clinical Research Network and Childhood Asthma Research and Education Network trials involving both adults and children with asthma. Collectively, these studies have helped refine the therapeutic role of existing controller medications, establish standard models for side-effect evaluation and risk-benefit models, validate symptom-based assessments for asthma control, and identify baseline characteristics that might predict individual patient responses. Remaining challenges include shaping the role of novel therapeutics in future guidelines, incorporating pharmacogenomic data in treatment decisions, and establishing better implementation strategies for translation to community settings, all with the goal of reducing the asthma burden on society.

Anti-Asthmatic Agents↗
PubMed1999

Artemisinin and its derivatives are transported by a vacuolar-network of Plasmodium falciparum and their anti-malarial activities are additive with toxic sphingolipid analogues that block the network.

There is great need to identify and characterize drug targets and chemotherapeutic strategies against malaria. Here we show that a vacuolar-network induced by the human malaria parasite Plasmodium falciparum, is a major import pathway for artemisinin, a leading, new anti-malarial that is known to be effective against drug resistant strains. We also show that artemisinin-treatment induces aberrant, budding of a vacuolar-network membrane protein and its antimalarial activity is additive with toxic sphingolipid analogues that block the network. The data suggest that artemisinin alters membrane protein export from the vacuolar-network and combinations with anti-network reagents have the potential to provide powerful new chemotherapy for drug resistant malaria.

Animals↗
PubMed2000

Real-time transmission of full-motion echocardiography over a high-speed data network: impact of data rate and network quality of service.

UNLABELLED: With high-resolution network transmission required for telemedicine, education, and guided-image acquisition, the impact of errors and transmission rates on image quality needs evaluation. METHODS: We transmitted clinical echocardiograms from 2 National Aeronautics and Space Administration (NASA) research centers with the use of Motion Picture Expert Group-2 (MPEG-2) encoding and asynchronous transmission mode (ATM) network protocol over the NASA Research and Education Network. Data rates and network quality (cell losses [CLR], errors [CER], and delay variability [CVD]) were altered and image quality was judged. RESULTS: At speeds of 3 to 5 megabits per second (Mbps), digital images were superior to those on videotape; at 2 Mbps, images were equivalent. Increasing CLR caused occasional, brief pauses. Extreme CER and CDV increases still yielded high-quality images. CONCLUSIONS: Real-time echocardiographic acquisition, guidance, and transmission is feasible with the use of MPEG-2 and ATM with broadcast quality seen above 3 Mbps, even with severe network quality degradation. These techniques can be applied to telemedicine and used for planned echocardiography aboard the International Space Station.

Artifacts↗
PubMed2003

Learning rules and network repair in spike-timing-based computation networks.

Plasticity in connections between neurons allows learning and adaptation, but it also allows noise to degrade the function of a network. Ongoing network self-repair is thus necessary. We describe a method to derive spike-timing-dependent plasticity rules for self-repair, based on the firing patterns of a functioning network. These plasticity rules for self-repair also provide the basis for unsupervised learning of new tasks. The particular plasticity rule derived for a network depends on the network and task. Here, self-repair is illustrated for a model of the mammalian olfactory system in which the computational task is that of odor recognition. In this olfactory example, the derived rule has qualitative similarity with experimental results seen in spike-timing-dependent plasticity. Unsupervised learning of new tasks by using the derived self-repair rule is demonstrated by learning to recognize new odors.

Action Potentials↗
PubMed2005

Identification of networks of sexually transmitted infection: a molecular, geographic, and social network analysis.

BACKGROUND: Despite widespread efforts to control it, Chlamydia trachomatis remains the most frequently diagnosed bacterial sexually transmitted infection (STI). Analysis of sexual networks has been proposed as a novel tool for control of and research into STI. In the present study, we combine molecular genotype data, analysis of geographic clusters, and sociodemographic descriptors to facilitate analysis of large sexual networks. METHODS: Individual chlamydia genotypes found in Manitoba, Canada, were analyzed to identify geographic clusters, and the identified clusters were further characterized by statistical analysis of sociodemographic variables. RESULTS: A total of 10 geographic clusters of chlamydia-genotype infection were identified. Clusters in Winnipeg showed no or little geographic overlap and could be further differentiated on the basis of the sociodemographic characteristics of the individuals within a cluster. Several clusters in northern Manitoba overlapped geographically but, nonetheless, could be differentiated on the basis of the sociodemographic characteristics of the infected individuals. CONCLUSIONS: On the basis of results of the combined analyses, each geographic cluster appeared to represent a relatively distinct transmission network within the larger sexual network. The geographic analysis of the molecular data provided a basis for establishment of potential epidemiological connections between small groups of unlinked individuals. Analytic approaches of the type described here would help to decipher the patterns that exist within large social network data sets and would be applicable to many types of infectious agents.

Adolescent↗