Minimal Cut Sets and the Use of Failure Modes in Metabolic Networks

Clark, Sangaalofa Tooki; Verwoerd, W.S.

doi:10.3390/metabo2030567

Cited by 4 publications

(4 citation statements)

References 62 publications

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“…As opposed to many of methods described previously, extreme currents aim to increase dimensionality by describing non-decomposable EFMs situated both within and on the boundaries of the flux regions; these arise as a result of partitioning each reversible reaction into two irreversible reactions [37]. Minimal cut sets (MCSs) are another variant of EFMs that result in inactivity of the system with respect to the objective reaction if removed [38]. Therefore, they can be used to identify target genes and repress undesirable metabolic functions, whilst assessing the effect on the structure of the entire metabolic network.…”

Section: Unbiased Methodsmentioning

confidence: 99%

Seeing the wood for the trees: a forest of methods for optimization and omic-network integration in metabolic modelling

Vijayakumar

Conway

Lió

et al. 2017

Briefings in Bioinformatics

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Metabolic modelling has entered a mature phase with dozens of methods and software implementations available to the practitioner and the theoretician. It is not easy for a modeller to be able to see the wood (or the forest) for the trees. Driven by this analogy, we here present a 'forest' of principal methods used for constraint-based modelling in systems biology. This provides a tree-based view of methods available to prospective modellers, also available in interactive version at http://modellingmetabolism.net, where it will be kept updated with new methods after the publication of the present manuscript. Our updated classification of existing methods and tools highlights the most promising in the different branches, with the aim to develop a vision of how existing methods could hybridize and become more complex. We then provide the first hands-on tutorial for multi-objective optimization of metabolic models in R. We finally discuss the implementation of multi-view machine learning approaches in poly-omic integration. Throughout this work, we demonstrate the optimization of trade-offs between multiple metabolic objectives, with a focus on omic data integration through machine learning. We anticipate that the combination of a survey, a perspective on multi-view machine learning and a step-by-step R tutorial should be of interest for both the beginner and the advanced user.

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Section: Unbiased Methodsmentioning

confidence: 99%

Seeing the wood for the trees: a forest of methods for optimization and omic-network integration in metabolic modelling

Vijayakumar

Conway

Lió

et al. 2017

Briefings in Bioinformatics

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“…The reliability of a system is a numerical rating of how well it is expected to perform over a certain time frame. Most tools are constructed using algorithms that are minimum path set algorithms or minimal cut set algorithms (Negi et al 2022;Clark and Verwoerd 2012). Determining network reliance via a collection of minimum pathways or cuts is NP-hard, unfortunately.…”

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confidence: 99%

A comprehensive approach for assessing the reliability of complex networks using OANN approach

Taluja,

Solanki,

Kumar

2023

Multidiscip. Sci. J.

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The optimistic model of network reliability assumes the nodes to be trustworthy while assigning a failure probability to the network's connections. For calculating a network's reliability, the persistent condition is used to guarantee that no two edges have the same failure probability. Accurately estimating the network's reliability across all of its endpoints is an NP-hard problem. The study of network reliability centers on problems arising from topological isolation of individual data nodes. Analysis of network reliability spans the phases of building, deploying, and testing a network. Issues with connection, capacity, and trip time are all metrics used in analyses of computer network reliability. In this paper, an Optimal ANN strategy is proposed as a means of assessing the reliability of the network. In this research, we analyze the methods used in and findings from recent studies on trustworthiness. The term "Optimized Artificial Neural Network" (OANN) is used to describe a strategy that takes into account aspects of both neural networks and another way for measuring trustworthiness. Results are well tested on network of 2^8nodes (mesh network) and hyper-tree network of n nodes. A network's performance may be evaluated with the help of the suggested method, which also contributes to the calculation of its cost and reliability metrics.

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“…Minimal cut sets are complementary to EMs, and consist of the minimal sets of reactions that, when blocked, will repress a certain metabolic functionality by preventing the network from achieving steady state. A review of MCSs can be found in [3].…”

Section: Introductionmentioning

confidence: 99%

“…Based on this idea, we can use experimental results of compounds that are found in a particular tissue, or are conversely absent, to identify the viable EMs [4] [6] [7] and MCSs [3] [5] [8] for certain tissues and, subsequently, genes that are being expressed in terms of the reactions that are taking place. This will be cheaper and easier to use than practical experimental methods such as microarrays which need advanced experimental technology to carry out and are hard to repeat.…”

Section: Introductionmentioning

confidence: 99%

A Systems Approach for Determining Gene Expression from Experimental Observation of Compound Presence and Absence

Clark¹,

Verwoerd²

2014

ABB

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Different genes are expressed in different tissues, depending on functional objectives and selection pressures. Based on complete knowledge of the structure of the metabolic network and all the reactions taking place in the cell, elementary modes (EMs) and minimal cut sets (MCSs) can relate compounds observed in a tissue, to the genes being expressed by respectively providing the full set of non-decomposable routes of reactions and compounds that lead to the synthesis of external products, and the full set of possible target genes for blocking the synthesis of external products. So, for a particular tissue, only the EMs containing the reactions that are related to the genes being expressed in those tissues, are active for the production of the corresponding compounds. This concept is used to develop an algorithm for determining a matrix of reactions (which can be related to corresponding genes) taking place in a tissue, using experimental observations of compounds in a tissue. The program is applied to the Arabidopsis flower and identified 20 core reactions occurring in all the viable EMs. They originate from the trans-cinnamate compound and lead to the formation of kaempferol and quercetin compounds and their derivatives, as well as anthocyanin compounds. Analyses of the patterns in the matrix identify reaction sets related to certain functions such as the formation of derivatives of the two anthocyanin compounds present, as well as the reactions leading from the network's external substrate erythrose-4P to L-Phenyla-lanine, cinnamyl-alc to trans-cinnamate and so on. The program can be used to successfully determine genes taking place in a tissue, and the patterns in the resulting matrix can be analysed to determine gene sets and the state of the tissue.

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Minimal Cut Sets and the Use of Failure Modes in Metabolic Networks

Cited by 4 publications

References 62 publications

Seeing the wood for the trees: a forest of methods for optimization and omic-network integration in metabolic modelling

Seeing the wood for the trees: a forest of methods for optimization and omic-network integration in metabolic modelling

A comprehensive approach for assessing the reliability of complex networks using OANN approach

A Systems Approach for Determining Gene Expression from Experimental Observation of Compound Presence and Absence

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