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Metabolic modelling of microbes: the flux-balance approach
2002
Environmental Microbiology
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We would also like to thank Dr Kenneth Timmis for inviting us to write this minireview of our work. ...
Acknowledgements We would like to acknowledge Jason DiTonno and Purusharth Prakash for assistance with the figures. ...
Further analysis reveals that there are three failure modes: 1 failure to incorporate gene regulatory events (four genes: aceEF, eno, pfk, ppc); 2 failure to specify metabolic network demands correctly ...
doi:10.1046/j.1462-2920.2002.00282.x
pmid:12000313
fatcat:7nbdctxiqnarfhx73ck2snjvfe
Genome-scale microbial in silico models: the constraints-based approach
2003
Trends in Biotechnology
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For example, all possible steady state flux distributions through a metabolic network are bounded in a solution space formed by a set of unique basis pathways, called the 'extreme pathways [34] .' ...
The success rate of these predictions is typically in the order of 70 -90% depending on the organism studied and the type of prediction being made. ...
Experimental data (both measured internal flux distributions and predicted growth rate) provided evidence for the hypothesis that knockout strains of microorganisms do use their metabolic networks, at ...
doi:10.1016/s0167-7799(03)00030-1
pmid:12679064
fatcat:5p5voq3p3bbk7llr5vgjgjh2fu
It's a noisy business! Genetic regulation at the nanomolar scale
1999
Trends in Genetics
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PII: S0168-9525(98)01659-X 65 40 Ericson, J. et al. (1998) Integrated FGF and BMP signaling controls the progression of progenitor cell differentiation and the emergence of pattern in the embryonic anterior ...
Figure 3 (e) illustrates how mutations in one or more of the genes in a redundant regulatory network can increase the probability of failure of the network. ...
This approach to reliability analysis requires the consideration of the potential failure patterns of the regulatory network and not simply of individual genes or sets of redundant genes. ...
doi:10.1016/s0168-9525(98)01659-x
pmid:10098409
fatcat:dsuacvlke5b3vk4s6ia6mtlkuu
Transcriptional Regulation in Constraints-based Metabolic Models ofEscherichia coli
2002
Journal of Biological Chemistry
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and regulatory rules for the E. coli MG1655 in silico central metabolic/regulatory model. ...
These previous models do not account for regulation of gene transcription and thus cannot accurately predict some organism functions. ...
Acknowledgment-We thank Christophe Schilling for assistance in drawing the figures. ...
doi:10.1074/jbc.m201691200
pmid:12006566
fatcat:en3dauw3ebfrvnnv6emfpp67ma
The Emerging Paradigm of Network Medicine in the Study of Human Disease
2012
Circulation Research
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This review introduces the fundamental concepts of network medicine and explores the feasibility and potential impact of network-based methods for predicting individual manifestations of human disease ...
These network pathways are presumably regulated in a coordinated fashion, but such regulation has been difficult to decipher using only reductionistic principles. ...
Acknowledgments We thank Stephanie Tribuna for expert administrative assistance and Sol Chan for assistance with figures. ...
doi:10.1161/circresaha.111.258541
pmid:22821909
pmcid:PMC3425394
fatcat:m4zwmfv42vejrpd3kkbpx2k4h4
Text-mining assisted regulatory annotation
2008
Genome Biology
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We also thank ENFIN, the BioSapiens Network, the Research Foundation -Flanders (FWO-Vlaanderen), Genome Canada and Genome British Columbia for financial support of the RegCreative Jamboree. ...
We are especially grateful to Martin Krallinger, Lynette Hirschman, Alfonso Valencia and Ewan Birney for encouraging links between the regulatory informatics and text-mining communities. ...
This recovery rate of PDFs from PMID lists is slightly higher than a rate of 79.6% reported for papers on bacterial gene regulation [8] . ...
doi:10.1186/gb-2008-9-2-r31
pmid:18271954
pmcid:PMC2374703
fatcat:rplmnumegze4hg3kdc37tykuim
Network Analyses in Plant Pathogens
2018
Frontiers in Microbiology
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A scenario, where the application of systems biology constitutes a very powerful tool, is the study of interactions between hosts and pathogens using network approaches. ...
The review comprises metabolic simulation, protein-protein interactions, regulatory control of gene expression, hostpathogen modeling, and genome evolution in bacteria. ...
We also want to thank the Administrative Department of Science and Technology in Colombia (Colciencias) for the award under contract number 0794-2013 for support to CA. ...
doi:10.3389/fmicb.2018.00035
pmid:29441045
pmcid:PMC5797656
fatcat:ebka5yqikzhm7fqqgqfvojl7ra
Reconstructing gene regulatory networks: from random to scale-free connectivity
2006
IEE Proceedings - Systems Biology
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Recent evidence points to scale-free properties in biological networks, however, where network connectivity follows a power-law distribution. ...
Because this new approach does not make any assumptions about the distribution of network connections, it is suitable for application to scale-free networks. ...
A MATLAB program that implements the S2G and G2S algorithms is available on request to E.J.C. ...
doi:10.1049/ip-syb:20050092
pmid:16986626
fatcat:ews6vdpftjcqbiwjxd6buhysui
Failed "nonaccelerating" models of prokaryote gene regulatory networks
[article]
2004
arXiv
pre-print
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In this paper, we demonstrate that such network growth models are unable to explain recent comparative genomics results on the growth of prokaryote regulatory gene networks as a function of gene number ...
We develop two "nonaccelerating" network models of prokaryote regulatory gene networks in an endeavor to match observation and demonstrate that these approaches fail to reproduce observed statistics. ...
The accelerating and nonaccelerating models of prokaryote gene networks differ most markedly in their predictions for the age dependency of the distribution of inbound and outbound regulatory links. ...
arXiv:q-bio/0312022v2
fatcat:uz6t57db6fft3mnsjkmvrqzwfq
Optimal Experimental Design for Gene Regulatory Networks in the Presence of Uncertainty
2015
IEEE/ACM Transactions on Computational Biology & Bioinformatics
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Of major interest to translational genomics is the intervention in gene regulatory networks (GRNs) to affect cell behavior; in particular, to alter pathological phenotypes. ...
Index Terms Mean objective cost of uncertainty (MOCU), experimental design, gene regulatory network (GRN), network intervention. ! ...
Today, a salient objective of translational systems biology is to determine beneficial interventions in gene regulatory networks (GRNs) for the purpose of identifying potential drug targets. ...
doi:10.1109/tcbb.2014.2377733
pmid:26357334
fatcat:xxzdfqwz2rgubefpppdwddnbvi
Stability and Flexibility from a System Analysis of Gene Regulatory Networks Based on Ordinary Differential Equations
2011
The Open Bioinformatics Journal
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The inference of large-scale gene regulatory networks from high-throughput data sets has revealed a diverse picture of only partially overlapping descriptions. ...
Nevertheless, several properties in the organization of these networks are recurrent, such as hubs, a modular structure and certain motifs. ...
ACKNOWLEDGEMENTS The authors acknowledge financial support from CENIIT, the Centre for Industrial Information Technology at Linköping Institute of Technology, Sweden. ...
doi:10.2174/1875036201105010026
fatcat:rkhq7nuafzcuti4zqj6ezmmxda
Control Motifs for Intracellular Regulatory Networks
2001
Annual Review of Biomedical Engineering
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A number of approaches to identifying and analyzing control motifs in intracellular networks are reviewed. ...
A central goal of modern biology is to optimally use the data on these networks to understand how their design leads to the observed cellular behaviors and failures. ...
Furthermore, system failure, for both biological and engineered systems, can arise either from explicit loss in function, leading to total failure, or from a breakdown in the regulatory system, leading ...
doi:10.1146/annurev.bioeng.3.1.391
pmid:11447069
fatcat:day7ilkuwrcznpapvragyjzgdu
miRNA-target gene regulatory networks: A Bayesian integrative approach to biomarker selection with application to kidney cancer
2015
Biometrics
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Using the KIRC data, we confirm that biomarkers involved in regulatory networks are more likely to be associated with survival time, showing connections in one regulatory network for five out of six such ...
We propose a novel Bayesian model to identify microRNAs and their target genes that are associated with survival time by incorporating the microRNA regulatory network through prior distributions. ...
Stingo and Kim-Anh Do are partially supported by a Cancer Center Support Grant (NCI Grant P30 CA016672). ...
doi:10.1111/biom.12266
pmid:25639276
pmcid:PMC4499566
fatcat:rlbzuqdd5bft3hqmjmevi6nwv4
Inherent size constraints on prokaryote gene networks due to "accelerating" growth
[article]
2004
arXiv
pre-print
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This paper presents a probabilistic accelerating network model for prokaryotic gene regulation which closely matches observed statistics by employing two classes of network nodes (regulatory and non-regulatory ...
) and directed links whose inbound heads are exponentially distributed over all nodes and whose outbound tails are preferentially attached to regulatory nodes and described by a scale free distribution ...
Our approach reproducing accelerating network statistics for growing prokaryote genomes complements and informs alternate networking approaches seeking to deduce or simulate the regulatory networks of ...
arXiv:q-bio/0312021v2
fatcat:wjicc33wmbdu5a7jr7vr6nmcfy
Regulatory on/off minimization of metabolic flux changes after genetic perturbations
2005
Proceedings of the National Academy of Sciences of the United States of America
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Predicting the metabolic state of an organism after a gene knockout is a challenging task, because the regulatory system governs a series of transient metabolic changes that converge to a steadystate condition ...
Regulatory on͞off minimization (ROOM) is a constraint-based algorithm for predicting the metabolic steady state after gene knockouts. ...
We are grateful to Benny Chor for his comments on this work and to Daniel Segre for sharing data and ideas. ...
doi:10.1073/pnas.0406346102
pmid:15897462
pmcid:PMC1140402
fatcat:srpulbcfarct7pefjod25yjm4m
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