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Computer Communication Networks↗
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Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.
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[Telepathology: current problems and perspectives on development].
Telepathology is a rapidly developing discipline of XXI-century medical technology. Advantages, shortcomings and perspectives of this method are discussed.
Computer Communication Networks↗
Immunoinformatics--the new kid in town.
The astounding diversity of immune system components (e.g. immunoglobulins, lymphocyte receptors, or cytokines) together with the complexity of the regulatory pathways and network-type interactions makes im munology a combinatorial science. Currently available data represent only a tiny fraction of possible situations and data continues to accrue at an exponential rate. Computational analysis has therefore become an essential element of immunology research with a main role of immunoinformatics being the management and analysis of immunological data. More advanced analyses of the immune system using computational models typically involve conversion of an immunological question to a computational problem, followed by solving of the computational problem and translation of these results into biologically meaningful answers. Major immunoinformatics developments include immunological databases, sequence analysis, structure modelling, mathematical modelling of the immune system, simulation of laboratory experiments, statistical support for immunological experimentation and immunogenomics. In this paper we describe the status and challenges within these sub-fields. We foresee the emergence of immunomics not only as a collective endeavour by researchers to decipher the sequences of T cell receptors, immunoglobulins, and other immune receptors, but also to functionally annotate the capacity of the immune system to interact with the whole array of selfand non-self entities, including genome-to-genome interactions.
Allergy and Immunology↗
A "systematics" tool for medical terminologies.
Finding the hierarchical relations amongst multiple terms within medical terminologies that support multiple parents to a term is a common task, especially for trainees and knowledge engineers implementing or maintaining medical logic modules or guidelines. Examples of such terminologies include the UMLS and the Medical Entity Dictionary (MED). In addition, the task of identifying and discriminating amongst some common ancestors to a list of terms is a recurrent theme. This is also a common concern in the science of classification (systematics). Some nearest common ancestors have distinct valuable properties for classification and simplification of lists. Although there exist some visualized navigating and editing tools for the UMLS and the MED, they are browsers that show a large number of unrelated and irrelevant relationships to the task at hand. While algorithms have been well studied in computer science to solve such a problem over semantic networks and trees, to our knowledge, they have not been used with a visualization tool in biomedicine. We developed a visualized tool that graphically displays the hierarchical relations of multiple terms, and helps identifying the nearest common ancestors of these terms.
Classification↗
A collaborative institutional model for integrating computer applications in the medical curriculum.
The introduction and promotion of information technology in an established medical curriculum with existing academic and technical support structures poses a number of challenges. The UNC School of Medicine has developed the Taskforce on Educational Applications in Medicine (TEAM), to coordinate this effort. TEAM works as a confederation of existing research and support units with interests in computers and education, along with a core of interested faculty with curricular responsibilities. Constituent units of the TEAM confederation include the medical center library, medical television studios, basic science teaching laboratories, educational development office, microcomputer and network support groups, academic affairs administration, and a subset of course directors and teaching faculty. Among our efforts have been the establishment of (1) a mini-grant program to support faculty initiated development and implementation of computer applications in the curriculum, (2) a symposium series with visiting speakers to acquaint faculty with current developments in medical informatics and related curricular efforts at other institution, (3) 20 computer workstations located in the multipurpose teaching labs where first and second year students do much of their academic work, (4) a demonstration center for evaluation of courseware and technologically advanced delivery systems. The student workstations provide convenient access to electronic mail, University schedules and calendars, the CoSy computer conferencing system, and several software applications integral to their courses in pathology, histology, microbiology, biochemistry, and neurobiology. The progress achieved toward the primary goal has modestly exceeded our initial expectations, while the collegiality and interest expressed toward TEAM activities in the local environment stand as empirical measures of the success of the concept.
Academic Medical Centers↗
[Computer technology for bioimaging].
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Biological Science Disciplines↗
How do connectionist networks compute?
Although connectionism is advocated by its proponents as an alternative to the classical computational theory of mind, doubts persist about its computational credentials. Our aim is to dispel these doubts by explaining how connectionist networks compute. We first develop a generic account of computation-no easy task, because computation, like almost every other foundational concept in cognitive science, has resisted canonical definition. We opt for a characterisation that does justice to the explanatory role of computation in cognitive science. Next we examine what might be regarded as the "conventional" account of connectionist computation. We show why this account is inadequate and hence fosters the suspicion that connectionist networks are not genuinely computational. Lastly, we turn to the principal task of the paper: the development of a more robust portrait of connectionist computation. The basis of this portrait is an explanation of the representational capacities of connection weights, supported by an analysis of the weight configurations of a series of simulated neural networks.
Cognitive Science↗
Bionformation: untangling the networks of life.
The growth of numerous subdisciplines at the interface between biology and computer science paves the way for reconsidering the special relationship between information and life. In this sense, the term 'bioinformation' appears as an integrative notion that is useful to promote a new understanding of the heterogeneous networkings that characterize life. Two conceptual avenues are explored here: representation and symmetry. It is argued that the special organization of the living cell, based on the overlapping of both sequential and 'amorphous' architectures, endlessly strives to fill in the occurring 'functional voids' or symmetry breakings; and it endlessly produces physiological networkings and evolutionary novelties as a byproduct. Characterizing the special dynamics inherent in the living cell may be a precondition for understanding the information-production processes on which other emergent informational entities are based, particularly, nervous systems and societies.
Animals↗
Topology of the conceptual network of language.
We define two words in a language to be connected if they express similar concepts. The network of connections among the many thousands of words that make up a language is important not only for the study of the structure and evolution of languages, but also for cognitive science. We study this issue quantitatively, by mapping out the conceptual network of the English language, with the connections being defined by the entries in a Thesaurus dictionary. We find that this network presents a small-world structure, with an amazingly small average shortest path, and appears to exhibit an asymptotic scale-free feature with algebraic connectivity distribution.
Journal Article↗
Using neural networks to predict the onset of diabetes mellitus.
Classification is an important decision making tool, especially in the medical sciences. Unfortunately, while several classification procedures exist, many of the current methods fail to provide adequate results. In recent years, artificial neural networks have been suggested as an alternative tool for classification. Here, we use neural networks to predict the onset of diabetes mellitus in Pima Indian women. The modeling capabilities of neural networks are compared to traditional methods like logistic regression and to a specific method called ADAP, which has been used to predict diabetes. The results indicate that neural networks are indeed a viable approach to classification. Furthermore, we attempt to provide a basis upon which neural networks can be used for variable selection in statistical modeling.
Classification↗
A SOFM approach to predicting HIV drug resistance.
The self-organizing feature map (SOFM or SOM) neural network approach has been applied to a number of life sciences problems. In this paper, we apply SOFMs in predicting the resistance of the HIV virus to Saquinavir, an approved protease inhibitor. We show that a SOFM predicts resistance to Saquinavir with reasonable success based solely on the amino acid sequence of the HIV protease mutation. The best single network provided 69% coverage and 68% accuracy. We then combine a number of networks into various majority voting schemes. All of the combinations showed improved performance over the best single network, with an average of 85% coverage and 78% accuracy. Future research objectives are suggested based on these results.
Amino Acid Substitution↗
Inhaled nitric oxide therapy in neonatal hypoxic respiratory failure: insights beyond primary outcomes.
The Neonatal Research Network developed and initiated 3 multicenter randomized controlled clinical trials evaluating inhaled nitric oxide therapy. Additional projects evolved from these efforts including basic science research and observational investigations. This article provides a historical prospective of the Network's investigations related to the diagnosis and management of neonatal hypoxic respiratory failure, especially those related to inhaled nitric oxide therapy. It will review the Network's contributions toward advancing the clinical care of the newborn with severe hypoxic respiratory failure.
Administration, Inhalation↗
GaIN (Georgia Interactive Network for Medical Information) study on health professionals' search requests and continuing education needs.
Health sciences librarians are being called upon to be more proactive in their institutions' continuing education efforts. In an effort to identify whether search requests indicated CE needs, a study was conducted by a group of members of GaIN (Georgia Interactive Network for Medical Information). MEDLINE requests from health care professionals for subject specific clinical topics were collected during a six-month period via a standard search request form created for the study. Copies of all completed requests were collected and broad ICD-9 codes assigned to the search topics. Institutional reports were generated for each participating library to share with hospital CE coordinators. They were also compiled for the group as a whole, and reflected the "hottest" topics requested during the study period for physicians and for non-physicians (nurses, allied health, administrators). A survey to hospital librarians and CE educators showed some value in the reports, but greater potential for further collaboration between librarians and CE coordinators.
Allied Health Personnel↗
Natural histories of infectious disease: ecological vision in twentieth-century biomedical science.
During the twentieth century, disease ecology emerged as a distinct disciplinary network within infectious diseases research. The key figures were Theobald Smith, F. Macfarlane Burnet, René Dubos, and Frank Fenner. They all drew on Darwinian evolutionism to fashion an integrative (but rarely holistic) understanding of disease processes, distinguishing themselves from reductionist "chemists" and mere "microbe hunters." They sought a more complex, biologically informed epidemiology. Their emphasis on competition and mutualism in the animated environment differed from the physical determinism that prevailed in much medical geography and environmental health research. Disease ecology derived in part from studies of the interaction of organisms - micro and macro - in tropical medicine, veterinary pathology, and immunology. It developed in postcolonial settler societies. Once a minority interest, disease ecology has attracted more attention since the 1980s for its explanations of disease emergence, antibiotic resistance, bioterrorism, and the health impacts of climate change.
Biomedical Research↗
Toward a science of metabolic engineering.
Application of recombinant DNA methods to restructure metabolic networks can improve production of metabolite and protein products by altering pathway distributions and rates. Recruitment of heterologous proteins enables extension of existing pathways to obtain new chemical products, alter posttranslational protein processing, and degrade recalcitrant wastes. Although some of the experimental and mathematical tools required for rational metabolic engineering are available, complex cellular responses to genetic perturbations can complicate predictive design.
Amino Acids↗
Computer advances towards the realization of a cybernated health-science diagnostic system.
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Computer Communication Networks↗
Interactive modelling and simulation of biochemical networks.
The analysis of biochemical processes can be supported using methods of modelling and simulation. New methods of computer science are discussed in this field of research. This paper presents a new method which allows the modelling and analysis of complex metabolic networks. Moreover, our simulation shell is based on this formalization and represents the first tool for the interactive simulation of metabolic processes.
Biochemical Phenomena↗
Visualization of a cytoskeleton-like FtsZ network in chloroplasts.
It has been a long-standing dogma in life sciences that only eukaryotic organisms possess a cytoskeleton. Recently, this belief was questioned by the finding that the bacterial cell division protein FtsZ resembles tubulin in sequence and structure and, thus, may be the progenitor of this major eukaryotic cytoskeletal element. Here, we report two nuclear-encoded plant ftsZ genes which are highly conserved in coding sequence and intron structure. Both their encoded proteins are imported into plastids and there, like in bacteria, they act on the division process in a dose-dependent manner. Whereas in bacteria FtsZ only transiently polymerizes to a ring-like structure, in chloroplasts we identified persistent, highly organized filamentous scaffolds that are most likely involved in the maintenance of plastid integrity and in plastid division. As these networks resemble the eukaryotic cytoskeleton in form and function, we suggest the term "plastoskeleton" for this newly described subcellular structure.
Arabidopsis↗