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Quantitative Biology Of Metabolism

Author : H.-P. Bulnheim
ISBN : OCLC:925697467
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Quantitative Biology Of Metabolism

Author : International Symposium on Quantitative Biology of Metabolism
ISBN : MINN:319510000254355
Genre : Biochemistry
File Size : 28. 42 MB
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Quantitative Biology Of Metabolism

Author : Alfred Locker
ISBN : 9783642510656
Genre : Science
File Size : 68. 10 MB
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The development of the life sciences may be said to have effected a gradual transition from a more or less intuitive prescientific approach based on crude observation, via a more refined type of observation to experimentation and hence to the level of formal theories. Quantitative methods are introduced at the second level; they comprise: (a) quantitative design of experiments; (b) regrouping of experimental results; (c) evalua tion of results by means of mathematical or special statistical techniques. The last step implies the introduction of theoretical concepts, but we are not justified in speaking of theoretical science unless true theoretical con siderations-models or hypotheses-precede experiment, and this is then followed by an attempt to link results with theory so as to verify the theory. Biology at present seems to lie somewhere between the second and third level mentioned above, not yet having achieved the status of a theoretical science in all its branches. Thus, though the need for quantification and mathematical formulation is widely recognized, many biologists still believe that e.g. general systems theory is too abstract to be of use in handling concrete problems. Those, however, who look critically at the present state of affairs cannot adopt this attitude.

Quantitative Biology Of Metabolism

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ISBN : OCLC:248426975
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Quantitative Biology Of Metabolism

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ISBN : OCLC:1069275256
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Quantitative Biology Of Metabolism Proceedings Of The 3rd International Symposium

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ISBN : OCLC:840409303
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Quantitative Biology Of Metabolism

Author : Alfred Locker
ISBN : OCLC:610872066
Genre :
File Size : 85. 70 MB
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Quantitative Biology Of Metabolism

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ISBN : OCLC:1016282473
Genre : Metabolism
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Quantitative Biology Of Metabolism; Models Of Metabolism Metabolic Parameters Damage To Metabolism Metabolic Control; 3rd International Symposium Biologische Anstalt Helgoland September 26 29 1967 Organizers A Locker And F Kr?ger; Editor A Locker

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ISBN : LCCN:68055620
Genre : Metabolism
File Size : 70. 34 MB
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International Symposium On Quantitative Biology Of Metabolism 3rd

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ISBN : OCLC:853051686
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Quantitative Biology Of Metabolism

Author : International Symposium on Quantitative Biology of Metabolism 3d, Helgoland, 1967
ISBN : LCCN:nlm02000526
Genre : Adaptation (Physiology)
File Size : 90. 34 MB
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Quantitative Biology Of Metabolism

Author : International Symposium Biologische Staff
ISBN : 0387043012
Genre :
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Quantitative Biology Of Metabolism

Author : A. Locker
ISBN : OCLC:472202209
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International Symposium On Quantitative Biology Of Metabolism

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ISBN : OCLC:637846505
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Quantitative Biology Of Metabolism

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ISBN : OCLC:962970874
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Quantitative Biology Dynamics Of Living Systems

Author : Noriko Hiroi
ISBN : 9782889452132
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With the emergence of Systems Biology, there is a greater realization that the whole behavior of a living system may not be simply described as the sum of its elements. To represent a living system using mathematical principles, practical quantities with units are required. Quantities are not only the bridge between mathematical description and biological observations; they often stand as essential elements similar to genome information in genetics. This important realization has greatly rejuvenated research in the area of Quantitative Biology. Because of the increased need for precise quantification, a new era of technological development has opened. For example, spatio-temporal high-resolution imaging enables us to track single molecule behavior in vivo. Clever artificial control of experimental conditions and molecular structures has expanded the variety of quantities that can be directly measured. In addition, improved computational power and novel algorithms for analyzing theoretical models have made it possible to investigate complex biological phenomena. This research topic is organized on two aspects of technological advances which are the backbone of Quantitative Biology: (i) visualization of biomolecules, their dynamics and function, and (ii) generic technologies of model optimization and numeric integration. We have also included articles highlighting the need for new quantitative approaches to solve some of the long-standing cell biology questions. In the first section on visualizing biomolecules, four cutting-edge techniques are presented. Ichimura et al. provide a review of quantum dots including their basic characteristics and their applications (for example, single particle tracking). Horisawa discusses a quick and stable labeling technique using click chemistry with distinct advantages compared to fluorescent protein tags. The relatively small physical size, stability of covalent bond and simple metabolic labeling procedures in living cells provides this type of technology a potential to allow long-term imaging with least interference to protein function. Obien et al. review strategies to control microelectrodes for detecting neuronal activity and discuss techniques for higher resolution and quality of recordings using monolithic integration with on-chip circuitry. Finally, the original research article by Amariei et al. describes the oscillatory behavior of metabolites in bacteria. They describe a new method to visualize the periodic dynamics of metabolites in large scale cultures populations. These four articles contribute to the development of quantitative methods visualizing diverse targets: proteins, electrical signals and metabolites. In the second section of the topic, we have included articles on the development of computational tools to fully harness the potential of quantitative measurements through either calculation based on specific model or validation of the model itself. Kimura et al. introduce optimization procedures to search for parameters in a quantitative model that can reproduce experimental data. They present four examples: transcriptional regulation, bacterial chemotaxis, morphogenesis of tissues and organs, and cell cycle regulation. The original research article by Sumiyoshi et al. presents a general methodology to accelerate stochastic simulation efforts. They introduce a method to achieve 130 times faster computation of stochastic models by applying GPGPU. The strength of such accelerated numerical calculation are sometimes underestimated in biology; faster simulation enables multiple runs and in turn improved accuracy of numerical calculation which may change the final conclusion of modeling study. This also highlights the need to carefully assess simulation results and estimations using computational tools.

Quantitative Systems Biology For Engineering Organisms And Pathways

Author : Hilal Taymaz-Nikerel
ISBN : 9782889198290
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Studying organisms as a whole for potential metabolic(ally) engineering of organisms for production of (bio)chemicals is essential for industrial biotechnology. To this end, integrative analysis of different –omics measurements (transciptomics, proteomics, metabolomics, fluxomics) provides invaluable information. Combination of experimental top-down and bottom-up approaches with powerful analytical tools/techniques and mathematical modeling, namely (quantitative) systems biology, currently making the state of art of this discipline, is the only practice that would improve our understanding for the purpose. The use of high-throughput technologies induced the required development of many bioinformatics tools and mathematical methods for the integration of obtained data. Such research is significant since compiling information from different levels of a living system and connecting them is not an easy task. In particular, construction of dynamic models for product improvement has been one of the goals of many research groups. In this Research Topic, we summarize and bring a general review of the most recent and relevant contributions in quantitative systems biology applied in metabolic modeling perspective. We want to make special emphasis on the techniques that can be widely implemented in regular scientific laboratories and in those works that include theoretical presentations. With this Research Topic we discuss the importance of applying systems biology approaches for finding metabolic engineering targets for the efficient production of the desired biochemical integrating information from genomes and networks to industrial production. Examples and perspectives in the design of new industrially relevant chemicals, e.g. increased titer/productivity/yield of (bio)chemicals, are welcome. Addition to the founded examples, potential new techniques that would frontier the research will be part of this topic. The significance of multi ‘omics’ approaches to understand/uncover the pathogenesis/mechanisms of metabolic disesases is also one of the main topics.

Systems Biology Of Microbial Infection

Author : Reinhard Guthke
ISBN : 9782889190607
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The systems biology of microbial infections aims at describing and analysing the confrontation of the host with bacterial and fungal pathogens. It intends to understand and to model the interaction of the host, in particular the immune system of humans or animals, with components of pathogens. This comprises experimental studies that provide spatio-temporal data from monitoring the response of host and pathogenic cells to perturbations or when interacting with each other, as well as the integrative analysis of genome-wide data from both the host and the pathogen. In perspective, the host-pathogen interaction should be described by a combination of spatio-temporal models with interacting molecular networks of the host and the pathogen. The aim is to unravel the main mechanisms of pathogenicity, to identify diagnostic biomarkers and potential drug targets, and to explore novel strategies for personalized therapy by computer simulations. Some microorganisms are part of the normal microbial flora, existing either in a mutualistic or commensal relationship with the host. Microorganisms become pathogenic if they posses certain physiological characteristics and virulence determinants as well as capabilities for immune evasion. Despite the different pathogenesis of infections, there are several common traits: (1) Before infection, pathogens must be able to overcome (epithelial) barriers. The infection starts by adhesion and colonization and is followed by entering of the pathogen into the host through the mucosa or (injured) skin. (2) Next, infection arises if the pathogen multiplies and overgrows the normal microbial flora, either at the place of entrance or in deeper tissue layers or organs. (3) After the growth phase, the pathogen damages the host’s cells, tissues and organs by producing toxins or destructive enzymes. Thus, systems biology of microbial infection comprises all levels of the pathogen and the host’s immune system. The investigation may start with the pathogen, its adhesion and colonization at the host, its interaction with host cell types e.g. epithelia cells, dendritic cells, macrophages, neutrophils, natural killer cells, etc. Because infection diseases are mainly found in patients with a weakened immune system, e.g. reduced activities of immune effector cells or defects in the epithelial barriers, systems biology of infection can also start with modelling of the immune defence including innate and adaptive immunity. Systems biological studies comprise both experimental and theoretical approaches. The experimental studies may be dedicated to reveal the relevance of certain genes or proteins in the above mentioned processes on the side of the pathogen and/or the host by applying functional and biochemical analyses based on knock-out mutants and knock- down experiments. At the theoretical, i.e. mathematical and computational, side systems biology of microbial infection comprises: (1) modelling of molecular mechanisms of bacterial or fungal infections, (2) modelling of non-protective and protective immune defences against microbial pathogens to generate information for possible immune therapy approaches, (3) modelling of infection dynamics and identification of biomarkers for diagnosis and for individualized therapy, (4) identifying essential virulence determinants and thereby predicting potential drug targets.

Systems Biology

Author : Bernhard Ø. Palsson
ISBN : 9781316239940
Genre : Science
File Size : 75. 16 MB
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Recent technological advances have enabled comprehensive determination of the molecular composition of living cells. The chemical interactions between many of these molecules are known, giving rise to genome-scale reconstructed biochemical reaction networks underlying cellular functions. Mathematical descriptions of the totality of these chemical interactions lead to genome-scale models that allow the computation of physiological functions. Reflecting these recent developments, this textbook explains how such quantitative and computable genotype-phenotype relationships are built using a genome-wide basis of information about the gene portfolio of a target organism. It describes how biological knowledge is assembled to reconstruct biochemical reaction networks, the formulation of computational models of biological functions, and how these models can be used to address key biological questions and enable predictive biology. Developed through extensive classroom use, the book is designed to provide students with a solid conceptual framework and an invaluable set of modeling tools and computational approaches.

Theoretical And Applied Aspects Of Systems Biology

Author : Fabricio Alves Barbosa da Silva
ISBN : 9783319749747
Genre : Computers
File Size : 31. 52 MB
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This book presents the theoretical foundations of Systems Biology, as well as its application in studies on human hosts, pathogens and associated diseases. This book presents several chapters written by renowned experts in the field. Some topics discussed in depth in this book include: computational modeling of multiresistant bacteria, systems biology of cancer, systems immunology, networks in systems biology.

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