Hominoid evolution and environmental change in the Neogene of Europe: a European Science Foundation network.
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Using the Diagrammatic Cell Language trade mark, Gene Network Sciences (GNS) has created a network model of interconnected signal transduction pathways and gene expression networks that control human cell proliferation and apoptosis. It includes receptor activation and mitogenic signaling, initiation of cell cycle, and passage of checkpoints and apoptosis. Time-course experiments measuring mRNA abundance and protein activity are conducted on Caco-2 and HCT 116 colon cell lines. These data were used to constrain unknown regulatory interactions and kinetic parameters via sensitivity analysis and parameter optimization methods contained in the DigitalCell computer simulation platform. FACS, RNA knockdown, cell growth, and apoptosis data are also used to constrain the model and to identify unknown pathways, and cross talk between known pathways will also be discussed. Using the cell simulation, GNS tested the efficacy of various drug targets and performed validation experiments to test computer simulation predictions. The simulation is a powerful tool that can in principle incorporate patient-specific data on the DNA, RNA, and protein levels for assessing efficacy of therapeutics in specific patient populations and can greatly impact success of a given therapeutic strategy.
Recently there was an increased interest towards network approach to biology and environmental sciences. Networks are believed to be the key to the understanding of the work of biological machine in cells, organs, organisms, and ecosystems. While complexity of undirected networks has been recently analyzed, the assessment of complexity in directed networks has specificity that has not been explored so far. The present paper aims to address the existing gap by discussing the applicability of the available complexity descriptors. New specific measures (vertex accessibility, accessible connectedness, and adjusted average distance) are introduced based on assessment of the reduced accessibility of nodes in directed networks.
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A nation-wide ecosystem science network for Canada was formed in 1994. At that time, mercury was a re-emerging issue in Canada and the Coordinating Office for the network sought collaboration to assess the issue. The key mechanisms by which the network has added value in addressing this issue are: 1) Information Dissemination, the network has organised, facilitated and co-hosted a number of regional. national and international mercury events (meetings, conferences and workshops) which have served to bring the expertise together, the network also disseminates information on it's web page. and the Coordinating Office hosts an annual National Science Conference: 2) Collaborative Mercury Monitoring, network partners advocated the need for a single hemispheric mercury network which resulted in the development of a compatible Canada-U.S. mercury deposition network, which may also be expanded into Mexico, and 3) Environmental Reporting, the network has collaborated with others to report on current mercury findings through initiatives such as the 1998 Northeast States and Eastern Canadian Mercury Study, a 1999 Mercury Case Study and is presently a partner in the University of Quebec's proposal to form a Collaborative Mercury Ecosystem Research Network in Canada.
The article analyzes what philosophical implications actor-network theory may have in studies of the sciences. Actor-network theory has revitalized the debate on the sciences because it puts the focus on investigating science in action, that is, on science as it is actually practiced in the research laboratory. The concepts of subject and object, along with the concepts of truth, rationality, and scientific facts, are redefined from the perspective of actor-network theory. The article analyzes possible alliances between this theory and the philosophy of difference proposed by Deleuze, Guattari, and Serres.
Users of the IAIMS Knowledge Network at the Georgetown University Medical Center have access to multiple in-house and external databases from a single point of entry through BioSYNTHESIS. The IAIMS project has developed a rich environment of biomedical information resources that represent a medical decision support system for campus physicians and students. The BioSYNTHESIS system is an information navigator that provides transparent access to a Knowledge Network of over a dozen databases. These multiple health sciences databases consist of bibliographic, informational, diagnostic, and research systems which reside on diverse computers such as DEC VAXs, SUN 490, AT&T 3B2s, Macintoshes, IBM PC/PS2s and the AT&T ISN and SYTEK network systems. Ethernet and TCP/IP protocols are used in the network architecture. BioSYNTHESIS also provides network links to the other campus libraries and to external institutions. As additional knowledge resources and technological advances have become available. BioSYNTHESIS has evolved from a two phase to a three phase program. Major components of the system including recent achievements and future plans are described.
Leptin, a hormone produced by adipocytes, provides information on the availability of fat stores to the hypothalamus and acts as an afferent satiety signal regulating appetite and energy expenditure in both rodents and humans [Zhang Y, Proenca R, Maffei M, Barone M, Leopold L, Friedman JM. Positional cloning of the mouse obese gene and its human homologue. Nature 1994;372:425-432; Sinha MK. Human leptin: the hormone of adipose tissue. Eur J Endocrinol 1997;136:461-4; Campfield LA, Smith FJ, Guisez Y, Devos R, Burn P. Recombinant mouse ob protein: evidence for a peripheral signal linking adiposity and central neural networks. Science 1995;269:546-9; Halaas JL, Gajiwala KS, Maffei M, Cohen SL, Chait BT, Rabinowitz D, Lallone RL, Burley SK, Friedman JM. Weight-reducing effects of the plasma protein encoded by the obese gene. Science 1995;269:543-6; Saladin R, De Vos P, Guerre-Millo M, Leturque A, Girard J, Staels B, Auwern J. Transient increase in obese gene expression after food intake or insulin administration. Nature 1995;377:527-9; Campfield LA, Smith FJ, Burn P. The OB protein (leptin) pathway - a link between adipose tissue mass and central neural networks. Horm Metab Res 1996;28:619-632; Blum WF, Kiess W, Rascher W, editors. Leptin - the voice of the adipose tissue. J&J Edition, JA Barth Verlag, Heidelberg, 1997]. In addition, leptin is thought to play an important role for reproduction and during gestation [Kiess W, Blum WF, Aubert ML. Leptin, puberty and reproductive function: lessons from animal studies and observations in humans. Eur J Endocrinol 1997;138:1-4; Barash IA, Cheung CC, Wigle DS, Ren H, Kabitting EB, Kuijer JL, Clifton DK, Steiner RA. Leptin is a metabolic signal to the reproductive system. Endocrinology 1996;133:3144-47; Chehab F, Lim M, Lu R. Correction of the sterility defect in homozygous obese female mice by treatment with the human recombinant leptin. Nature Genetics 1996;12:318-20; Kiess W, Schubring C, Prohaska F, Englaro P, Rascher W, Attanasio A, Blum WF. Leptin in amniotic fluid at term and at midgestation. In: Blum WF, Kiess W, Rascher W, editors. Leptin - the voice of the adipose tissue. J&J Edition, JA Barth Verlag, Heidelberg, 1997]. The purpose of this study was to gain more insight into a putative role of leptin during midgestation. Therefore we have measured leptin concentrations in maternal serum and amniotic fluid using a specific radioimmunoassay (RIA) employing human recombinant leptin for tracer and standard preparation [Blum WF, Kiess W, Rascher W, editors, Leptin - The voice of the adipose tissue. J&J Edition, JA Barth Verlag, Heidelberg, 1997; Blum WF, Englaro P, Heiman M, Attanasio Am, Kiess W, Rascher W. Clinical studies of serum leptin. In: Blum WF, Kiess W, Rascher W. Leptin - The voice of the adipose tissue. J&J Edition, JA Barth Verlag, Heidelberg, 1997; Blum WF, Englaro P, Heiman M, Attanasio AM, Kiess W, Rascher W. Plasma leptin levels in healthy children and adolescents: dependence on body mass index, body fat mass, gender, pubertal stage and testosterone. J Clin Endocrinol Metab 1997;82:2904-2910]. In addition, estriol, hCG and alphafetoprotein were measured in maternal serum. (ABSTRACT TRUNCATED)
The advancement of modelling and simulation within complex scientific applications is currently constrained by the rate at which knowledge can be extracted from the data produced. As Grid computing evolves, new means of increasing the efficiency of data analysis are being explored. RealityGrid aims to enable more efficient use of scientific computing resources within the condensed matter, materials and biological science communities. The Imperial College e-Science Networked Infrastructure (ICENI) Grid middleware provides an end-to-end pipeline that simplifies the stages of computation, simulation and collaboration. The intention of this work is to allow all scientists to have access to these features without the need for heroic efforts that have been associated with this sort of work in the past. Scientists can utilise advanced scheduling mechanisms to ensure efficient planning of computations, visualize and interactively steer simulations and securely collaborate with colleagues via the Access Grid through a single integrated middleware application.
This article examines the role of computation and quantitative methods in modern biomedical research to identify emerging scientific, technical, policy and organizational trends. It identifies common concerns and practices in the emerging community of computationally-oriented bio-scientists by reviewing a national symposium, Digital Biology: the Emerging Paradigm, held at the National Institutes of Health in Bethesda, Maryland, November 6th and 7th 2003. This meeting showed how biomedical computing promises scientific breakthroughs that will yield significant health benefits. Three key areas that define the emerging discipline of digital biology are: scientific data integration, multi-scale modeling and networked science. Each area faces unique technical challenges and information policy issues that must be addressed as the field matures. Here we summarize the emergent challenges and offer suggestions to academia, industry and government on how best to expand the role of computation in their scientific activities.
Compartments in food webs are subgroups of taxa in which many strong interactions occur within the subgroups and few weak interactions occur between the subgroups. Theoretically, compartments increase the stability in networks, such as food webs. Compartments have been difficult to detect in empirical food webs because of incompatible approaches or insufficient methodological rigour. Here we show that a method for detecting compartments from the social networking science identified significant compartments in three of five complex, empirical food webs. Detection of compartments was influenced by food web resolution, such as interactions with weights. Because the method identifies compartmental boundaries in which interactions are concentrated, it is compatible with the definition of compartments. The method is rigorous because it maximizes an explicit function, identifies the number of non-overlapping compartments, assigns membership to compartments, and tests the statistical significance of the results. A graphical presentation reveals systemic relationships and taxa-specific positions as structured by compartments. From this graphic, we explore two scenarios of disturbance to develop a hypothesis for testing how compartmentalized interactions increase stability in food webs.
The identification of general principles relating structure to dynamics has been a major goal in the study of complex networks. We propose that the special case of linear network dynamics provides a natural framework within which a number of interesting yet tractable problems can be defined. We report the emergence of modularity and hierarchical organization in evolved networks supporting asymptotically stable linear dynamics. Numerical experiments demonstrate that linear stability benefits from the presence of a hierarchy of modules and that this architecture improves the robustness of network stability to random perturbations in network structure. This work illustrates an approach to network science which is simultaneously structural and dynamical in nature.