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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
ENG
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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...

Philosophical Basis and Some Historical Aspects of Systems Biology: From Hegel to Noble - Applications for Bioenergetic Research

Saks, Valdur; Monge, Claire; Guzun, Rita
Fonte: Molecular Diversity Preservation International (MDPI) Publicador: Molecular Diversity Preservation International (MDPI)
Tipo: Artigo de Revista Científica
Publicado em 13/03/2009 EN
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We live in times of paradigmatic changes for the biological sciences. Reductionism, that for the last six decades has been the philosophical basis of biochemistry and molecular biology, is being displaced by Systems Biology, which favors the study of integrated systems. Historically, Systems Biology - defined as the higher level analysis of complex biological systems - was pioneered by Claude Bernard in physiology, Norbert Wiener with the development of cybernetics, and Erwin Schrödinger in his thermodynamic approach to the living. Systems Biology applies methods inspired by cybernetics, network analysis, and non-equilibrium dynamics of open systems. These developments follow very precisely the dialectical principles of development from thesis to antithesis to synthesis discovered by Hegel. Systems Biology opens new perspectives for studies of the integrated processes of energy metabolism in different cells. These integrated systems acquire new, system-level properties due to interaction of cellular components, such as metabolic compartmentation, channeling and functional coupling mechanisms, which are central for regulation of the energy fluxes. State of the art of these studies in the new area of Molecular System Bioenergetics is analyzed.

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 EN
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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...

‘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
EN
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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’.

Review and application of group theory to molecular systems biology

Rietman, Edward A; Karp, Robert L; Tuszynski, Jack A
Fonte: BioMed Central Publicador: BioMed Central
Tipo: Artigo de Revista Científica
Publicado em 22/06/2011 EN
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In this paper we provide a review of selected mathematical ideas that can help us better understand the boundary between living and non-living systems. We focus on group theory and abstract algebra applied to molecular systems biology. Throughout this paper we briefly describe possible open problems. In connection with the genetic code we propose that it may be possible to use perturbation theory to explore the adjacent possibilities in the 64-dimensional space-time manifold of the evolving genome.

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 EN
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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
EN
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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 EN
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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 emerging genomics and systems biology research lead to systems genomics studies

Yang, Mary Qu; Yoshigoe, Kenji; Yang, William; Tong, Weida; Qin, Xiang; Dunker, A Keith; Chen, Zhongxue; Arbania, Hamid R; Liu, Jun S; Niemierko, Andrzej; Yang, Jack Y
Fonte: BioMed Central Publicador: BioMed Central
Tipo: Artigo de Revista Científica
EN_US
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Synergistically integrating multi-layer genomic data at systems level not only can lead to deeper insights into the molecular mechanisms related to disease initiation and progression, but also can guide pathway-based biomarker and drug target identification. With the advent of high-throughput next-generation sequencing technologies, sequencing both DNA and RNA has generated multi-layer genomic data that can provide DNA polymorphism, non-coding RNA, messenger RNA, gene expression, isoform and alternative splicing information. Systems biology on the other hand studies complex biological systems, particularly systematic study of complex molecular interactions within specific cells or organisms. Genomics and molecular systems biology can be merged into the study of genomic profiles and implicated biological functions at cellular or organism level. The prospectively emerging field can be referred to as systems genomics or genomic systems biology. The Mid-South Bioinformatics Centre (MBC) and Joint Bioinformatics Ph.D. Program of University of Arkansas at Little Rock and University of Arkansas for Medical Sciences are particularly interested in promoting education and research advancement in this prospectively emerging field. Based on past investigations and research outcomes...

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 EN
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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...

Estrategias de ingeniería metabólica y biología de sistemas aplicadas a la producción de L(-)carnitina por Escherichia coli= Metabolic engineering and systems biology strategies for L(-)carnitine production in Escherichia coli

Arense Parra, Paula
Fonte: Universidade de Múrcia Publicador: Universidade de Múrcia
Tipo: Tese de Doutorado Formato: application/pdf
SPA; ENG
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Esta Tesis Doctoral recoge el trabajo de investigación que se ha realizado en dos líneas desarrolladas de forma paralela sobre Escherichia coli. Por un lado, la optimización de un proceso de biotransformación para mejorar la síntesis de L( )-carnitina mediante técnicas de ingeniería metabólica. Y por otro, la determinación de los principales efectos que provoca la exposición prolongada a altas concentraciones de sal y su respuesta de adaptación, principalmente cuando las fuentes de carbono pueden contener altas concentraciones de sal y tanto el sustrato como el producto son osmoprotectores. Para ello, se han aplicado técnicas utilizadas por la biología de sistemas y la ingeniería metabólica. La importancia de L( )-carnitina viene determinada por el papel que desempeña en el metabolismo energético, de hecho su deficiencia está asociada a diversas patologías. Varios trabajos centrados en la aplicación terapéutica de L( )-carnitina han demostrado que su administración puede ayudar a suplir dicha carencia. A partir de este punto, comienza una creciente actividad investigadora centrada en la producción de L( )-carnitina. Este trabajo presenta un método alternativo basado en la utilización de E. coli para llevar a cabo la biotransformación de compuestos de bajo valor añadido como puede ser D(+)-carnitina y/o crotonobetaína en L( )-carnitina. Por medio de técnicas de biología molecular se ha modificado genéticamente una cepa de E. coli...

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)
EN
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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...

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
ENG
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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...

Network Dynamics and Systems Biology

Norrell, Johannes Adrie
Fonte: Universidade Duke Publicador: Universidade Duke
Tipo: Dissertação Formato: 2947765 bytes; application/pdf
Publicado em //2009 EN_US
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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...

Systems biology of energetic and atomic costs in the yeast transcriptome, proteome, and metabolome

Michael D. Barton; Balazs Papp; Daniela Delneri; Stephen G. Oliver; Magnus Rattray; Casey M. Bergman
Fonte: Nature Preceedings Publicador: Nature Preceedings
Tipo: Manuscript
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Background: Every protein has a variable atomic and energetic cost to the cell based on the synthesis of its constituent amino acids. Quantifying the cost of amino acid synthesis is challenging, however natural selection is expected to favour the use of proteins whose constituents are cheaper to produce in terms of energetic and atomic cost. Results: We develop a systems biology approach to estimate the cost of amino acid synthesis based on genome-scale metabolic models, and directly investigate the effects of the cost of amino acid synthesis on transcriptomic, proteomic and metabolomic data in Saccharomyces cerevisiae. We used our two new and six previously reported measures of amino acid cost in conjunction with codon usage bias, tRNA gene number and atomic composition to identify the factors that predict transcript, protein and free amino acid levels in the yeast cell. While most previously reported cost measures are highly correlated, we find that our systems approach to formulating the cost of amino acid synthesis produces a novel measure of cost, which explains similar levels of variation in gene expression. Regardless of the measure used, the cost of amino acid synthesis is weakly associated with transcript and protein levels...

Beyond Structure: KiSAO and TEDDY -- Two Ontologies Addressing Pragmatical and Dynamical Aspects of Computational Models in Systems Biology

Dagmar Köhn; Nicolas Le Novère; Christian Knüpfer
Fonte: Nature Preceedings Publicador: Nature Preceedings
Tipo: Poster
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Computational models are becoming more and more the central scientific paradigm for understanding the complexity of living systems. With the increasing number and size of these models there is a growing need for model reuse and exchange. Furthermore, detailed models are not manageable without computer support. There are efforts to formalise the mathematical structure of models (e.g. SBML) and to standardise the kinetic and biological meaning of model components (e.g. SBO, GO, UniProt). However, formalising only the structure of computational models is not sufficient to easily exchange and reuse models and to achieve full computer support for modelling. We also need to formalise the pragmatical and dynamical aspects of models. For this purpose we propose two ontologies: The _Kinetic Simulation Algorithm Ontology_ (KiSAO) and the _TErminology for the Description of DYnamics_ (TEDDY). KiSAO covers algorithms used for simulation of computational models. The ontology classifies and puts into context existing simulation algorithms. For the classification, it uses several criteria such as deterministic/stochastic or spatial/nonspatial. The aim of TEDDY is to provide terms for describing and characterising dynamical behaviours...

ABC SMC for parameter estimation and model selection with applications in systems biology

Tina Toni
Fonte: Nature Preceedings Publicador: Nature Preceedings
Tipo: Conferência ou Objeto de Conferência
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666.7116%
Approximate Bayesian Computation (ABC) methods can be used in situations where the evaluation of the likelihood is computationally prohibitive. They are thus ideally suited for analyzing the complex dynamical models encountered in systems biology, where knowledge of the full (approximate) posterior is often essential. This talk gives an overview of an ABC algorithm based on Sequential Monte Carlo (ABC SMC). Different uses of the algorithm will be presented, depending on the application question of interest. The first is the general parameter estimation framework, where the interest lies in estimating the posterior parameter distribution from available experimental data. In the second context we ask whether the model can reproduce a desired qualitative or semi-quantitative behavior, and what dynamic behaviors the system can achieve. The third context discussed here for use of the ABC SMC algorithm is that of model selection. Here we ask which of the models (i.e. model topologies) from a pool of proposed candidate models represents the most suitable hypothesis about the biological system of interest. The focus of the presentation is applications of ABC SMC to questions from systems biology. ABC SMC is applied to a variety of biological models...

A Systems Biology Approach to the Evolution of Codon Use Pattern

Ines Thiele; Ronan M. T. Fleming; Richard Que; Aarash Bordbar; Bernhard O. Palsson
Fonte: Nature Preceedings Publicador: Nature Preceedings
Tipo: Manuscript
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The genetic code is redundant as amino acids are encoded by synonymous codons that are unequally used.This codon usage bias (CUB) affects gene expression and cellular functions yet the underlying mechanisms have not been elucidated. We used a sequence-specific, stoichiometric model of metabolism and macromolecular synthesis for Escherichia coli K12 MG1655 to test the effect of randomly changed CUB on growth maximization under various environmental conditions. Amongst CUB mutant strains, we identified reduced growth phenotypes, which were caused by tRNA supply shortage. We propose, supported by computations and bibliomic data, that expansion of tRNA gene content or tRNA reading is a mechanism to respond to changes in CUB. Our systems biology modelling framework suggests that in order to maximize growth and to adapt to new environmental niches, CUB and tRNA content must co-evolve and provides further evidence for the mutation-selection-drift balance theory of CUB.

Systems Biology on Bio-Linux

Mesude Bicak
Fonte: Nature Preceedings Publicador: Nature Preceedings
Tipo: Conferência ou Objeto de Conferência
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This presentation introduces the Bio-Linux Operating System which is a popular Computational Biology workstation with 500+ bioinformatics software. It then provides an overview of popular modelling approaches in systems biology, covering top-down, bottom-up and hybrid modelling. Finally it highlights the challenges being faced by systems biology modellers, agent-based modellers in particular, regarding standardisation efforts.

Complex Systems Biology of Organisms

I. C. Baianu
Fonte: Nature Preceedings Publicador: Nature Preceedings
Tipo: Manuscript
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Complex Systems Biology models and theories are axiomatically defined in terms of concrete categories and organismic supercategories (OS) to include both complete self-reproduction of logically defined pi-entities founded in Quine's logic and dynamic system diagrams subject to both algebraic and topological transformations. Mathematical models of complex organisms are expressed in terms of category theory and organismic supercategories (OS). OS theories have applications in: Bioinformatics, Developmental Biology, Genomics and Molecular Cell Biology