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Multi-objective Optimisation, Sensitivity and Robustness Analysis in FBA Modelling
[chapter]
2012
Lecture Notes in Computer Science
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We introduce a multi-objective optimisation algorithm, called Genetic Design through Multi-Objective (GDMO), and test it in several organisms to maximise the production of key intermediate metabolites ...
Finally, we perform the Sensitivity Analysis of the metabolic model, which finds the inputs with the highest influence on the outputs of the model. ...
Sensitivity Analysis In modelling, Sensitivity Analysis (SA) is a method used to discover which inputs play a key role on the output of the model. ...
doi:10.1007/978-3-642-33636-2_9
fatcat:ginxwnbsj5azxnfz7v7depn4vu
Robust design of microbial strains
2012
Bioinformatics
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Our framework performs three tasks: it evaluates the parameter sensitivity of the microbial model, searches for the optimal genetic or fluxes design, and finally calculates the robustness of the microbial ...
In this work, we present a computational framework that searches for optimal and robust microbial strains that are able to produce target molecules. ...
In this work, we perform SA to find the most sensitive pathways in the FBA model of E. coli. ...
doi:10.1093/bioinformatics/bts590
pmid:23044547
fatcat:skldltn7b5dtlo4wxuwwxuzg5y
Seeing the wood for the trees: a forest of methods for optimization and omic-network integration in metabolic modelling
2017
Briefings in Bioinformatics
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We then provide the first hands-on tutorial for multi-objective optimisation of metabolic models in R. ...
Throughout this work, we demonstrate the optimisation of trade-offs between multiple metabolic objectives, with a focus on omic data integration through machine learning. ...
Although several pipelines are available in Matlab and Python, this is the first tutorial available in R for multi-objective optimisation of FBA models. ...
doi:10.1093/bib/bbx053
pmid:28575143
fatcat:wcoccaxi5fhjjju7pimdx4w2oe
GEESE: Metabolically driven latent space learning for gene expression data
[article]
2018
bioRxiv
pre-print
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We evaluated the proposed framework, showing its ability to capture biologically relevant features, and encoding that features in a much simpler latent space. ...
We showed how using a metabolic model to drive the autoencoder learning process helps in achieving better generalisation to unseen data. ...
We performed sensitivity analysis to obtain the robustness value of each gene for two different objectives. ...
doi:10.1101/365643
fatcat:hqsoib44qbfyxlhzau674wakpq
The Era of Big Data: Genome-scale Modelling meets Machine Learning
2020
Computational and Structural Biotechnology Journal
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With omics data being generated at an unprecedented rate, genome-scale modelling has become pivotal in its organisation and analysis. ...
We discuss the latest advances in genome-scale modelling and the development of optimisation algorithms for network and error reduction, intracellular constraining and applications to strain design. ...
RB thanks the UK Biotechnology and Biological Sciences Research Council and GlaxoSmithKline for his studentship. ...
doi:10.1016/j.csbj.2020.10.011
pmid:33240470
pmcid:PMC7663219
fatcat:nvzko7mayzc67eqkfnf25c7fni
A constraint-based modelling approach to metabolic dysfunction in Parkinson's disease
2015
Computational and Structural Biotechnology Journal
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Relationships between competing functions
ORCA functions
Model-driven discovery
Multi-objective based sensitivity analysis to identify reactions supporting the
neurophysiological activities
ORCA ...
Robustness analysis can give an insight into the relationship between available energy sources and enzyme fluxes at an objective-oriented metabolic state. ...
doi:10.1016/j.csbj.2015.08.002
pmid:26504511
pmcid:PMC4579274
fatcat:xpax7qdzsfeznaeqwn6u5njkcm
Discovering Essential Multiple Gene Effects through Large Scale Optimization: an Application to Human Cancer Metabolism
2020
IEEE/ACM Transactions on Computational Biology & Bioinformatics
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to find pairs and higher-order combinations of genetic modifications that simultaneously optimize multi-objective cellular goals. ...
Towards understanding the broader role of metabolism on cellular decision-making in health and disease conditions, it is important to integrate the study of metabolism with other core regulatory systems ...
Bilevel optimisation with transcriptomics In order to add transcriptomic information to an FBA model in a quantitative fashion, we model the effect of each gene expression profile as a change in the lower ...
doi:10.1109/tcbb.2020.2973386
pmid:32248120
fatcat:plx2b6ylmbhnlbzd6e5w5s5v34
Modelling microbial communities: harnessing consortia for biotechnological applications
2021
Computational and Structural Biotechnology Journal
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Microbes propagate and thrive in complex communities, and there are many benefits to studying and engineering microbial communities instead of single strains. ...
In this review, we discuss key principles of microbial interactions, followed by a deep dive into genome-scale metabolic models, focussing on a vast repertoire of constraint-based modelling methods that ...
Fig. 4 . 4 A schematic of constraint-based modelling using flux balance analysis (FBA). ...
doi:10.1016/j.csbj.2021.06.048
pmid:34584635
pmcid:PMC8441623
fatcat:23mbuti53nbz7aonpukurnw3ri
Model reduction of genome-scale metabolic models as a basis for targeted kinetic models
2021
Metabolic Engineering
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Using these minimal models of metabolism could allow for further exploration of dynamic responses in metabolic networks. ...
Here we show that these reduced size models can be representative of the dynamics of the original model and demonstrate the automated generation and parameterisation of such models. ...
We used multi-start local optimisation (fmincon, 100 starts, 1000 maximum iterations), with a log-likelihood objective function as described in Fröhlich et al. (2017b) . ...
doi:10.1016/j.ymben.2021.01.008
pmid:33486094
fatcat:lrx52awtizcdtl44kqjec5blxq
Design and strain selection criteria for bacterial communication networks
2013
Nano Communication Networks
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In the next sections, we describe the methodology for designing strains (Pareto fronts and flux balance analysis (FBA)), ...
First, by using a multi-objective optimisation procedure, we search for the optimal trade off between energy production, which is a requirement for the motility, and the biomass growth, which is related ...
Given r objective functions f 1 , ..., f r to optimise, the problem of optimising in a multi-objective fashion can be formalised as where x is the variable in the search space. ...
doi:10.1016/j.nancom.2013.08.001
fatcat:rmt3opszkrdc3n63hjrncn3swu
Design and strain selection criteria for bacterial communication networks
[article]
2015
bioRxiv
pre-print
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First, by using a multi-objective optimisation procedure, we search for the optimal trade off between energy production, which is a requirement for the motility, and the biomass growth, which is related ...
We use flux balance analysis of genome-scale biochemical network of Escherichia coli k-13 MG1655. ...
Given r objective functions f 1 , ..., f r to optimise, the problem of optimising in a multi-objective fashion can be formalised as where x is the variable in the search space. ...
doi:10.1101/013383
fatcat:kmujdflf6bhlznsbqbf6hviaue
Systems biology
2010
Resonance
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His research interests include the modelling of complex biological networks and the analysis of their robustness and evolvability. ...
Her current research interests are in computational systems biology, cell modeling and structural bioinformatics and in applying these to address fundamental issues in drug discovery. ...
Robustness and fragility have been described in the literature as inseparable; the 'robust, yet fragile' nature of complex systems is thought to exhibit 'highly optimised tolerance'. ...
doi:10.1007/s12045-010-0015-7
fatcat:i7hbkuu35zhbbj2mltkoe6wmwq
Gene-centric constraint of metabolic models
[article]
2017
bioRxiv
pre-print
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Motivation: A number of approaches have been introduced in recent years allowing gene expression data to be integrated into the standard Flux Balance Analysis (FBA) technique. ...
This additional information permits greater accuracy in the prediction of intracellular fluxes, even when knowledge of the growth medium and biomass composition is incomplete, and allows exploration of ...
Acknowledgement Funding : This work was supported by the Biotechnology and Biological Sciences Research Council of the United Kingdom (NF and CC: grant BB/I00713X/2). ...
doi:10.1101/116558
fatcat:k6dsmii645d7vkbynkdkn4nphm
Systems Biology Approaches Toward Understanding Primary Mitochondrial Diseases
2019
Frontiers in Genetics
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In addition, "bottom-up" systems approaches have been adopted for use in the iterative cycle of systems biology: from data generation to model prediction and validation. ...
These disorders are multi-genic and multi-phenotypic (even within the same gene defect) and span the entire age range from prenatal to late adult onset. ...
ACKNOWLEDGMENTS The authors acknowledge research grant funding from Great Ormond Street Hospital Children's Charity, the NIHR Great Ormond Street Hospital Biomedical Research Centre, and the Lily Foundation ...
doi:10.3389/fgene.2019.00019
pmid:30774647
pmcid:PMC6367241
fatcat:vz66h37wbbftjjws3ntlrud7pe
Evolutionary Systems Biology of Amino Acid Biosynthetic Cost in Yeast
2010
PLoS ONE
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In the economy of the yeast cell, we find that the cost of amino acid synthesis plays a limited role in shaping transcript and protein expression levels compared to that of translational optimisation. ...
In order to optimise growth and reproduction, natural selection is expected, where possible, to favour the use of proteins whose constituents are cheaper to produce, as reduced biosynthetic cost may confer ...
Wall for providing the yeast sequence alignments; Evangelos Simeonidis for discussion of flux balance analysis; Leo Zeef, Juan Castrillo, Pinar Pir and Andy Hayes for helpful discussion of the transcriptomic ...
doi:10.1371/journal.pone.0011935
pmid:20808905
pmcid:PMC2923148
fatcat:7fw7bfpflvgt3aoqzvawzzroo4
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