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‣ Complex networks: the key to systems biology

COSTA, Luciano da Fontoura; RODRIGUES, Francisco A.; CRISTINO, Alexandre S.
Fonte: Sociedade Brasileira de Genética Publicador: Sociedade Brasileira de Genética
Tipo: Artigo de Revista Científica
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Though introduced recently, complex networks research has grown steadily because of its potential to represent, characterize and model a wide range of intricate natural systems and phenomena. Because of the intrinsic complexity and systemic organization of life, complex networks provide a specially promising framework for systems biology investigation. The current article is an up-to-date review of the major developments related to the application of complex networks in biology, with special attention focused on the more recent literature. The main concepts and models of complex networks are presented and illustrated in an accessible fashion. Three main types of networks are covered: transcriptional regulatory networks, protein-protein interaction networks and metabolic networks. The key role of complex networks for systems biology is extensively illustrated by several of the papers reviewed.; FAPESP; CNPq

‣ Exploring the multifactorial nature of autism through computational systems biology: Calcium and the Rho GTPase RAC1 under the spotlight

Zeidán-Chuliá, Fares; Rybarczyk-Filho, José Luiz; Salmina, Alla B.; De Oliveira, Ben-Hur Neves; Noda, Mami; Moreira, José Cláudio F.
Fonte: Universidade Estadual Paulista Publicador: Universidade Estadual Paulista
Tipo: Revisão Formato: 364-383
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Autism is a neurodevelopmental disorder characterized by impaired social interaction and communication accompanied with repetitive behavioral patterns and unusual stereotyped interests. Autism is considered a highly heterogeneous disorder with diverse putative causes and associated factors giving rise to variable ranges of symptomatology. Incidence seems to be increasing with time, while the underlying pathophysiological mechanisms remain virtually uncharacterized (or unknown). By systematic review of the literature and a systems biology approach, our aims were to examine the multifactorial nature of autism with its broad range of severity, to ascertain the predominant biological processes, cellular components, and molecular functions integral to the disorder, and finally, to elucidate the most central contributions (genetic and/or environmental) in silico. With this goal, we developed an integrative network model for gene-environment interactions (GENVI model) where calcium (Ca2+) was shown to be its most relevant node. Moreover, considering the present data from our systems biology approach together with the results from the differential gene expression analysis of cerebellar samples from autistic patients, we believe that RAC1, in particular...

‣ Modeling formalisms in systems biology

Machado, C. D.; Costa, Rafael S.; Rocha, Miguel; Ferreira, E. C.; Tidor, Bruce; Rocha, I.
Fonte: Springer Publicador: Springer
Tipo: Artigo de Revista Científica
Publicado em //2011 Português
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Systems Biology has taken advantage of computational tools and high-throughput experimental data to model several biological processes. These include signaling, gene regulatory, and metabolic networks. However, most of these models are specific to each kind of network. Their interconnection demands a whole-cell modeling framework for a complete understanding of cellular systems. We describe the features required by an integrated framework for modeling, analyzing and simulating biological processes, and review several modeling formalisms that have been used in Systems Biology including Boolean networks, Bayesian networks, Petri nets, process algebras, constraint-based models, differential equations, rule-based models, interacting state machines, cellular automata, and agent-based models. We compare the features provided by different formalisms, and discuss recent approaches in the integration of these formalisms, as well as possible directions for the future.

‣ Complex networks: the key to systems biology

Costa,Luciano da F.; Rodrigues,Francisco A.; Cristino,Alexandre S.
Fonte: Sociedade Brasileira de Genética Publicador: Sociedade Brasileira de Genética
Tipo: Artigo de Revista Científica Formato: text/html
Publicado em 01/01/2008 Português
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Though introduced recently, complex networks research has grown steadily because of its potential to represent, characterize and model a wide range of intricate natural systems and phenomena. Because of the intrinsic complexity and systemic organization of life, complex networks provide a specially promising framework for systems biology investigation. The current article is an up-to-date review of the major developments related to the application of complex networks in biology, with special attention focused on the more recent literature. The main concepts and models of complex networks are presented and illustrated in an accessible fashion. Three main types of networks are covered: transcriptional regulatory networks, protein-protein interaction networks and metabolic networks. The key role of complex networks for systems biology is extensively illustrated by several of the papers reviewed.

‣ Systems biology approach to study the high altitude adaptation in tibetans

De,Bi; Huajun,Xiao; Cuihong,Zhou; Jun,Zhou; Xiaoyan,Deng; Xiaopeng,Liu
Fonte: Instituto de Tecnologia do Paraná - Tecpar Publicador: Instituto de Tecnologia do Paraná - Tecpar
Tipo: Artigo de Revista Científica Formato: text/html
Publicado em 01/02/2013 Português
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The aim of this work was to study an integrative systems biology research strategy to construct a network including the protein-protein interactions (PPIs) and microRNAs (miRNAs) and identify the functional biological processes and pathways for high-altitude adaptation in Tibetans. The pathway enrichment analysis revealed that the genes in the network were mainly involved in signling the pathways and the function of microRNAs was concentrated in the signling pathways, which suggested that miRNAs might contribute to the Tibetans high-altitude adaptation through the participation in signaling pathway. These results contribute to better understanding on the high-altitude adaptation of the Tibetans.

‣ VirtualPlant: A Software Platform to Support Systems Biology Research1[W][OA]

Katari, Manpreet S.; Nowicki, Steve D.; Aceituno, Felipe F.; Nero, Damion; Kelfer, Jonathan; Thompson, Lee Parnell; Cabello, Juan M.; Davidson, Rebecca S.; Goldberg, Arthur P.; Shasha, Dennis E.; Coruzzi, Gloria M.; Gutiérrez, Rodrigo A.
Fonte: American Society of Plant Biologists Publicador: American Society of Plant Biologists
Tipo: Artigo de Revista Científica
Publicado em /02/2010 Português
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Data generation is no longer the limiting factor in advancing biological research. In addition, data integration, analysis, and interpretation have become key bottlenecks and challenges that biologists conducting genomic research face daily. To enable biologists to derive testable hypotheses from the increasing amount of genomic data, we have developed the VirtualPlant software platform. VirtualPlant enables scientists to visualize, integrate, and analyze genomic data from a systems biology perspective. VirtualPlant integrates genome-wide data concerning the known and predicted relationships among genes, proteins, and molecules, as well as genome-scale experimental measurements. VirtualPlant also provides visualization techniques that render multivariate information in visual formats that facilitate the extraction of biological concepts. Importantly, VirtualPlant helps biologists who are not trained in computer science to mine lists of genes, microarray experiments, and gene networks to address questions in plant biology, such as: What are the molecular mechanisms by which internal or external perturbations affect processes controlling growth and development? We illustrate the use of VirtualPlant with three case studies, ranging from querying a gene of interest to the identification of gene networks and regulatory hubs that control seed development. Whereas the VirtualPlant software was developed to mine Arabidopsis (Arabidopsis thaliana) genomic data...

‣ Ten questions about systems biology

Joyner, Michael J; Pedersen, Bente K
Fonte: Blackwell Science Inc Publicador: Blackwell Science Inc
Tipo: Artigo de Revista Científica
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In this paper we raise ‘ten questions’ broadly related to ‘omics’, the term systems biology, and why the new biology has failed to deliver major therapeutic advances for many common diseases, especially diabetes and cardiovascular disease. We argue that a fundamentally narrow and reductionist perspective about the contribution of genes and genetic variants to disease is a key reason ‘omics’ has failed to deliver the anticipated breakthroughs. We then point out the critical utility of key concepts from physiology like homeostasis, regulated systems and redundancy as major intellectual tools to understand how whole animals adapt to the real world. We argue that a lack of fluency in these concepts is a major stumbling block for what has been narrowly defined as ‘systems biology’ by some of its leading advocates. We also point out that it is a failure of regulation at multiple levels that causes many common diseases. Finally, we attempt to integrate our critique of reductionism into a broader social framework about so-called translational research in specific and the root causes of common diseases in general. Throughout we offer ideas and suggestions that might be incorporated into the current biomedical environment to advance the understanding of disease through the perspective of physiology in conjunction with epidemiology as opposed to bottom-up reductionism alone.

‣ ‘Integrative Physiology 2.0’: integration of systems biology into physiology and its application to cardiovascular homeostasis

Kuster, Diederik W D; Merkus, Daphne; van der Velden, Jolanda; Verhoeven, Adrie J M; Duncker, Dirk J
Fonte: Blackwell Science Inc Publicador: Blackwell Science Inc
Tipo: Artigo de Revista Científica
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Since the completion of the Human Genome Project and the advent of the large scaled unbiased ‘-omics’ techniques, the field of systems biology has emerged. Systems biology aims to move away from the traditional reductionist molecular approach, which focused on understanding the role of single genes or proteins, towards a more holistic approach by studying networks and interactions between individual components of networks. From a conceptual standpoint, systems biology elicits a ‘back to the future’ experience for any integrative physiologist. However, many of the new techniques and modalities employed by systems biologists yield tremendous potential for integrative physiologists to expand their tool arsenal to (quantitatively) study complex biological processes, such as cardiac remodelling and heart failure, in a truly holistic fashion. We therefore advocate that systems biology should not become/stay a separate discipline with ‘-omics’ as its playing field, but should be integrated into physiology to create ‘Integrative Physiology 2.0’.

‣ Aspen Lung Conference 2010: Systems Biology of Lung Diseases—Progress in the Omics Era

Sheppard, Dean
Fonte: American Thoracic Society Publicador: American Thoracic Society
Tipo: Artigo de Revista Científica
Publicado em 01/05/2011 Português
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The 53rd annual Thomas L. Petty Aspen Lung Conference focused on the dramatic progress that has been made in the past several years in applying large-scale, unbiased data acquisition (“omics”) to the study of lung biology and disease. The conference organizers, Mark Geraci, Ivor Douglas, Stephen Rennard, and David Schwartz, put together a terrific program, and the invited speakers and participants presented data describing the rapid evolution of experimental approaches that should encourage pulmonary scientists to begin to think about a true molecular systems biology of the lung.

‣ Targeted Systems Biology Profiling of Tomato Fruit Reveals Coordination of the Yang Cycle and a Distinct Regulation of Ethylene Biosynthesis during Postclimacteric Ripening1[C][W][OA]

Van de Poel, Bram; Bulens, Inge; Markoula, Aikaterina; Hertog, Maarten L.A.T.M.; Dreesen, Rozemarijn; Wirtz, Markus; Vandoninck, Sandy; Oppermann, Yasmin; Keulemans, Johan; Hell, Ruediger; Waelkens, Etienne; De Proft, Maurice P.; Sauter, Margret; Nicolai,
Fonte: American Society of Plant Biologists Publicador: American Society of Plant Biologists
Tipo: Artigo de Revista Científica
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The concept of system 1 and system 2 ethylene biosynthesis during climacteric fruit ripening was initially described four decades ago. Although much is known about fruit development and climacteric ripening, little information is available about how ethylene biosynthesis is regulated during the postclimacteric phase. A targeted systems biology approach revealed a novel regulatory mechanism of ethylene biosynthesis of tomato (Solanum lycopersicum) when fruit have reached their maximal ethylene production level and which is characterized by a decline in ethylene biosynthesis. Ethylene production is shut down at the level of 1-aminocyclopropane-1-carboxylic acid oxidase. At the same time, 1-aminocyclopropane-1-carboxylic acid synthase activity increases. Analysis of the Yang cycle showed that the Yang cycle genes are regulated in a coordinated way and are highly expressed during postclimacteric ripening. Postclimacteric red tomatoes on the plant showed only a moderate regulation of 1-aminocyclopropane-1-carboxylic acid synthase and Yang cycle genes compared with the regulation in detached fruit. Treatment of red fruit with 1-methylcyclopropane and ethephon revealed that the shut-down mechanism in ethylene biosynthesis is developmentally programmed and only moderately ethylene sensitive. We propose that the termination of autocatalytic ethylene biosynthesis of system 2 in ripe fruit delays senescence and preserves the fruit until seed dispersal.

‣ Systems Biology in the study of Neurological Disorders: Focus on Alzheimer’s Disease

Pasinetti, Giulio M.; Hiller-Sturmhöfel, Susanne
Fonte: National Institute on Alcohol Abuse and Alcoholism Publicador: National Institute on Alcohol Abuse and Alcoholism
Tipo: Artigo de Revista Científica
Publicado em //2008 Português
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Systems biology approaches may be useful for studying the mechanisms underlying alcohol’s harmful effects on the brain. Such approaches already are used in the study of Alzheimer’s disease (AD), a progressive neurodegenerative disorder that, with the overall increase in life expectancy, will affect an increasing proportion of the population and become an increasingly serious public health concern. Systems biology approaches such as complementary DNA (cDNA) microarray analyses have helped identify several genes whose expression is altered in patients exhibiting the earliest stages of AD. Several of these genes are involved in the release of messenger molecules from the ends of nerve cells (i.e., in synaptic vesicle functioning), and their particular role in AD must be investigated further using conventional molecular biological approaches. Similarly, protein array analyses have identified candidate proteins that may play a role in the development of AD. Finally, proteomic approaches, such as certain mass spectrometry techniques, have been used to search for biomarkers of the progression from normal cognitive functioning to mild cognitive impairment and AD, which eventually may allow early and reliable diagnosis of the disease. These approaches already have yielded some candidate molecules whose validity and reliability as biomarkers of AD...

‣ The systems biology simulation core algorithm

Keller, Roland; Dörr, Alexander; Tabira, Akito; Funahashi, Akira; Ziller, Michael J; Adams, Richard; Rodriguez, Nicolas; Novère, Nicolas Le; Hiroi, Noriko; Planatscher, Hannes; Zell, Andreas; Dräger, Andreas
Fonte: BioMed Central Publicador: BioMed Central
Tipo: Artigo de Revista Científica
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Background: With the increasing availability of high dimensional time course data for metabolites, genes, and fluxes, the mathematical description of dynamical systems has become an essential aspect of research in systems biology. Models are often encoded in formats such as SBML, whose structure is very complex and difficult to evaluate due to many special cases. Results: This article describes an efficient algorithm to solve SBML models that are interpreted in terms of ordinary differential equations. We begin our consideration with a formal representation of the mathematical form of the models and explain all parts of the algorithm in detail, including several preprocessing steps. We provide a flexible reference implementation as part of the Systems Biology Simulation Core Library, a community-driven project providing a large collection of numerical solvers and a sophisticated interface hierarchy for the definition of custom differential equation systems. To demonstrate the capabilities of the new algorithm, it has been tested with the entire SBML Test Suite and all models of BioModels Database. Conclusions: The formal description of the mathematics behind the SBML format facilitates the implementation of the algorithm within specifically tailored programs. The reference implementation can be used as a simulation backend for Java™-based programs. Source code...

‣ Systems biology of ovine intestinal parasite resistance: disease gene modules and biomarkers

Kadarmideen, H.; Watson-Haigh, N.; Andronicos, N.
Fonte: Royal Society of Chemistry Publicador: Royal Society of Chemistry
Tipo: Artigo de Revista Científica
Publicado em //2011 Português
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This study reports on the molecular systems biology of gastrointestinal nematode (GIN) infection and potential biomarkers for GIN resistance in sheep. Microarray gene expression data were obtained for 3 different tissues at 4 time points from sheep artificially challenged with two types of nematodes, Haemonchus contortus (HC) and Trichostrongylus colubriformis (TC). We employed an integrated systems biology approach, integrating 3 main methods: standard differential gene expression analyses, weighted gene co-expression network analyses (WGCNA) and quantitative genetic analyses of gene expression traits of key biomarkers. Using standard differential gene expression analyses we identified differentially expressed genes (DE) which responded differently in sheep challenged with HC compared to those challenged with TC. These interaction genes (e.g. MRPL51, SMEK2, CAT, MAPK1IP1 and SLC25A20A) were enriched in Wnt receptor signalling pathway (p = 0.0132) and positive regulation of NFκβ transcription factor activity (p = 0.00208). We report FCER1A, a gene encoding a high-affinity receptor for the Fc region of immunoglobulin E, which is linked to innate immunity to GIN in sheep. Using weighted gene co-expression network analysis (WGCNA) methods...

‣ Parameter identifiability of biochemical reaction networks in systems biology

Geffen, Dara
Fonte: Quens University Publicador: Quens University
Tipo: Tese de Doutorado Formato: 1324816 bytes; application/pdf
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In systems biology, models often contain a large number of unknown or only roughly known parameters that must be estimated through the fitting of data. This work examines the question of whether or not these parameters can in fact be estimated from available measurements. Structural or a priori identifiability of unknown parameters in biochemical reaction networks is considered. Such systems consist of continuous time, nonlinear differential equations. Several methods for analyzing identifiability of such systems exist, most of which restate the question as one of observability by expanding the state space to include parameters. However, these existing methods were not developed with biological systems in mind, so do not necessarily address the specific challenges posed by this type of problem. In this work, such methods are considered for the analysis of a representative biological system, the NF-kappaB signal transduction pathway. It is shown that existing observability-based strategies, which rely on finding an analytical solution, require significant simplifications to be applicable to systems biology problems that are seldom feasible. The analytical nature of the solution imposes restrictions on the size and complexity of systems that these methods can handle. This conflicts with the fact that most currently studied systems biology models are rather large networks containing many states and parameters. In this thesis...

‣ Transcriptomics and systems biology analysis in identification of specific pathways involved in cacao resistance and susceptibility to witches' broom disease.

HORA JUNIOR, B. T. da; POLONI, J. de F.; LOPES, M. A.; DIAS, C. V.; GRAMACHO, K. P.; SCHUSTER, IVAN; SABAU, X.; CASCARDO, J. C. de M.; DI MAURO, S. M. Z.; GESTEIRA, A. da S.; BONATTOC, D.; MICHELI, F.
Fonte: Molecular BioSystems, February 2012. Publicador: Molecular BioSystems, February 2012.
Tipo: Artigo em periódico indexado (ALICE)
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This study reports on expression analysis associated with molecular systems biology of cacao-Moniliophthora perniciosa interaction. Gene expression data were obtained for two cacao genotypes (TSH1188, resistant; Catongo, susceptible) challenged or not with the fungus M. perniciosa and collected at three time points through disease. Using expression analysis, we identified 154 and 227 genes that are differentially expressed in TSH1188 and Catongo, respectively. The expression of some of these genes was confirmed by RT-qPCR. Physical protein-protein interaction (PPPI) networks of Arabidopsis thaliana orthologous proteins corresponding to resistant and susceptible interactions were obtained followed by cluster and gene ontology analyses. The integrated analysis of gene expression and systems biology allowed designing a general scheme of major mechanisms associated with witches' broom disease resistance/susceptibility. In this sense, the TSH1188 cultivar shows strong production of ROS and elicitors at the beginning of the interaction with M. perniciosa followed by resistance signal propagation and ROS detoxification. On the other hand, the Catongo genotype displays defense mechanisms that include the synthesis of some defense molecules but without success in regards to elimination of the fungus. This phase is followed by the activation of protein metabolism which is achieved with the production of proteasome associated with autophagy as a precursor mechanism of PCD. This work also identifies candidate genes for further functional studies and for genetic mapping and marker assisted selection.; 2012; Received 11th October 2011...

‣ Application of Computational Systems Biology to Explore Environmental Toxicity Hazards

Audouze, Karine; Grandjean, Philippe
Fonte: National Institute of Environmental Health Sciences Publicador: National Institute of Environmental Health Sciences
Tipo: Artigo de Revista Científica
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Background: Computer-based modeling is part of a new approach to predictive toxicology. Objectives: We investigated the usefulness of an integrated computational systems biology approach in a case study involving the isomers and metabolites of the pesticide dichlorodiphenyltrichloroethane (DDT) to ascertain their possible links to relevant adverse effects. Methods: We extracted chemical–protein association networks for each DDT isomer and its metabolites using ChemProt, a disease chemical biology database that includes both binding and gene expression data, and we explored protein–protein interactions using a human interactome network. To identify associated dysfunctions and diseases, we integrated protein–disease annotations into the protein complexes using the Online Mendelian Inheritance in Man database and the Comparative Toxicogenomics Database. Results: We found 175 human proteins linked to p,p'-DDT, and 187 to o,p'-DDT. Dichlorodiphenyldichloroethylene (p,p'-DDE) was the metabolite with the highest number of links, with 52. We grouped proteins for each compound based on their disease annotations. Although the two data sources differed in linkage to diseases, integrated results predicted that most diseases were linked to the two DDT isomers. Asthma was uniquely linked with p...

‣ Systems Biology Elucidates Common Pathogenic Mechanisms between Nonalcoholic and Alcoholic-Fatty Liver Disease

Sookoian, Silvia Cristina; Pirola, Carlos Jose
Fonte: Public Library Science Publicador: Public Library Science
Tipo: info:eu-repo/semantics/article; info:ar-repo/semantics/artículo; info:eu-repo/semantics/publishedVersion Formato: application/pdf
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The abnormal accumulation of fat in the liver is often related either to metabolic risk factors associated with metabolic syndrome in the absence of alcohol consumption (nonalcoholic fatty liver disease, NAFLD) or to chronic alcohol consumption (alcoholic fatty liver disease, AFLD). Clinical and histological studies suggest that NAFLD and AFLD share pathogenic mechanisms. Nevertheless, current data are still inconclusive as to whether the underlying biological process and disease pathways of NAFLD and AFLD are alike. Our primary aim was to integrate omics and physiological data to answer the question of whether NAFLD and AFLD share molecular processes that lead to disease development. We also explored the extent to which insulin resistance (IR) is a distinctive feature of NAFLD. To answer these questions, we used systems biology approaches, such as gene enrichment analysis, protein?protein interaction networks, and gene prioritization, based on multi-level data extracted by computational data mining. We observed that the leading disease pathways associated with NAFLD did not significantly differ from those of AFLD. However, systems biology revealed the importance of each molecular process behind each of the two diseases, and dissected distinctive molecular NAFLD and AFLD-signatures. Comparative co-analysis of NAFLD and AFLD clarified the participation of NAFLD...

‣ Systems biology approaches to bioremediation

Lorenzo, Víctor de
Fonte: Elsevier Publicador: Elsevier
Tipo: Artículo Formato: 6080 bytes; image/gif
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Bioremediation involves the exposure of a whole mixture of chemical structures to an intricate multispecies metabolic network present in a polluted scenario. The complexity involved in such events is growingly amenable to the conceptual frame and the tools of systems biology. The availability of genes, genomes, and metagenomes of biodegradative micro-organisms make it possible to model and even predict the fate of chemicals through the global metabolic network that results from connecting all known biochemical transactions. Microbial communities thus embody a landscape of pan-enzymes that is shaped by the freely diffusible metabolic pool (epimetabolome). Recent computational resources increasingly help the design of superior biocatalysts for biodegradation and biotransformations of desired chemicals, an objective that capitalizes on the new field of synthetic biology.; The work in Author's Laboratory is funded by contracts of the 6th and 7th Framework Programme of the EU and grants of the Spanish Ministry of Science and Innovation.; Peer reviewed

‣ Computational Systems Biology of Saccharomyces cerevisiae Cell Growth and Division

Mayhew, Michael Benjamin
Fonte: Universidade Duke Publicador: Universidade Duke
Tipo: Dissertação
Publicado em //2014 Português
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Cell division and growth are complex processes fundamental to all living organisms. In the budding yeast, Saccharomyces cerevisiae, these two processes are known to be coordinated with one another as a cell's mass must roughly double before division. Moreover, cell-cycle progression is dependent on cell size with smaller cells at birth generally taking more time in the cell cycle. This dependence is a signature of size control. Systems biology is an emerging field that emphasizes connections or dependencies between biological entities and processes over the characteristics of individual entities. Statistical models provide a quantitative framework for describing and analyzing these dependencies. In this dissertation, I take a statistical systems biology approach to study cell division and growth and the dependencies within and between these two processes, drawing on observations from richly informative microscope images and time-lapse movies. I review the current state of knowledge on these processes, highlighting key results and open questions from the biological literature. I then discuss my development of machine learning and statistical approaches to extract cell-cycle information from microscope images and to better characterize the cell-cycle progression of populations of cells. In addition...

‣ Network Dynamics and Systems Biology

Norrell, Johannes Adrie
Fonte: Universidade Duke Publicador: Universidade Duke
Tipo: Dissertação Formato: 2947765 bytes; application/pdf
Publicado em //2009 Português
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The physics of complex systems has grown considerably as a field in recent decades, largely due to improved computational technology and increased availability of systems level data. One area in which physics is of growing relevance is molecular biology. A new field, systems biology, investigates features of biological systems as a whole, a strategy of particular importance for understanding emergent properties that result from a complex network of interactions. Due to the complicated nature of the systems under study, the physics of complex systems has a significant role to play in elucidating the collective behavior.

In this dissertation, we explore three problems in the physics of complex systems, motivated in part by systems biology. The first of these concerns the applicability of Boolean models as an approximation of continuous systems. Studies of gene regulatory networks have employed both continuous and Boolean models to analyze the system dynamics, and the two have been found produce similar results in the cases analyzed. We ask whether or not Boolean models can generically reproduce the qualitative attractor dynamics of networks of continuously valued elements. Using a combination of analytical techniques and numerical simulations...