Calculation of theoretical yields in metabolic networks*

Shastri, Avantika A.; Morgan, John P.

doi:10.1002/bmb.2004.494032050379

Cited by 9 publications

(2 citation statements)

References 4 publications

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“…The derivation of the reaction sequence from the figures of Biochemical Atlas [12] does not guarantee obtaining either the real or an optimal pathway. This could be improved using an approach based on stoichiometric matrices [51,52] which would include multiple alternative pathways and might allow numerical determination of the optimum. The determination of the stoichiometric balance of each reaction from graphical representations is prone to error.…”

Section: Discussionmentioning

confidence: 99%

Stoichiometric estimates of the biochemical conversion efficiencies in tsetse metabolism

Custer

2005

BMC Ecol

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Background: The time varying flows of biomass and energy in tsetse (Glossina) can be examined through the construction of a dynamic mass-energy budget specific to these flies but such a budget depends on efficiencies of metabolic conversion which are unknown. These efficiencies of conversion determine the overall yields when food or storage tissue is converted into body tissue or into metabolic energy. A biochemical approach to the estimation of these efficiencies uses stoichiometry and a simplified description of tsetse metabolism to derive estimates of the yields, for a given amount of each substrate, of conversion product, by-products, and exchanged gases. This biochemical approach improves on estimates obtained through calorimetry because the stoichiometric calculations explicitly include the inefficiencies and costs of the reactions of conversion. However, the biochemical approach still overestimates the actual conversion efficiency because the approach ignores all the biological inefficiencies and costs such as the inefficiencies of leaky membranes and the costs of molecular transport, enzyme production, and cell growth.

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Section: Discussionmentioning

confidence: 99%

Stoichiometric estimates of the biochemical conversion efficiencies in tsetse metabolism

Custer

2005

BMC Ecol

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“…The latest edition of Brock's microbiology, the most commonly employed textbook in the undergraduate microbiology course includes just the calculation of growth rate in the chapter on microbial metabolism (Madigan et al 2015). Several reports (Bergevin 2010;Feser, Vasaly, and Herrera 2013;Marsteller 2010), books Phillips, Kondev, and Theriot 2016), examples (Alberty 1991;Flamholz et al 2014;Milo 2013;Planinšič and Vollmer 2008;Sender, Fuchs, and Milo 2016;Shastri and Morgan 2004;Torres 1998) and online tools (Adamec 2017;J. L. Koenig 2017;Shah et al 2013;"Math Bench" 2016;"QUBESHome" 2016; "Science in the Classroom" 2017) have been published showcasing the importance of quantitative approach in biological studies.…”

Section: Introductionmentioning

confidence: 99%

Elucidating the Importance of Numeracy Skills for Undergraduate Students in Life Sciences Using the Oxygen Requirement in Yeast as an Example

Raghavendran¹,

Olavarria²,

Gombert³

2018

Preprint

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2Current education in biology is devoid of mathematics in many countries, probably because many relevant biological processes are explained from a qualitative point of view rather than addressing the quantitative aspects of these phenomena. Here, we employ a case study from the yeast physiology to illustrate the importance of numeracy skills for a deeper understanding of relevant biological problems. Yeast anaerobic growth on sugars is a widespread process as it is the basis for beer, bread, and winemaking and it is much akin to lactic acid fermentation in muscle cells in response to an increased energy demand. To study the physiology of yeasts under controlled conditions and being able to compare the results quantitatively, one ought to perform measurements and calculations involving concentrations of oxygen, biomass, and organic compounds. To set-up an "anaerobic" culture of Saccharomyces cerevisiae in a defined medium, one needs to calculate how much oxygen must enter the cultivation system, to meet the requirements for ergosterol and oleic acid biosyntheses, both of which require oxygen. Using basic physicochemical principles and simple mathematical skills, students will be able to compute the oxygen requirement for yeast growth under such "anaerobic" conditions.

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Integration of Metabolic Knowledge for Genome‐Scale Metabolic Reconstruction

Masoudi‐Nejad

Salehzadeh‐Yazdi

Akbari‐Birgani

et al. 2013

Biological Knowledge Discovery Handbook

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INTRODUCTIONGenome-scale metabolic reconstruction is the ultimate goal of system biologists for finding out the genotype-phenotype relationship. For achieving this purpose, we need enough knowledge about the metabolic pathways and genome annotation. During the present study, we aim to describe the foundational concepts, central to omics data, model formulation, history, method, and applications of metabolic network reconstruction as well as some related sources. In Section 45.2, we describe omics data and high-throughput technologies for gaining these data. In section 45.3, we present different ways for metabolic network modeling. In section 45.4, we summarize the history of genome-scale modeling as one of the most important methods for metabolic network modeling. In sections 45.5 and 45.6, we elucidate how genome-scale metabolic models could be generated and what their applications are. Finally, in section 45.7, we review biochemical pathways and genome annotation databases. OMICs ERAInnovative omics technologies such as genomics, transcriptomics, proteomics, and metabolomics facilitate a strategy toward the simultaneous analysis of the large number of genes, transcripts, proteins, and metabolites. Therefore, a huge volume of data has generated about the make-up of cells and their behavior at various cellular levels and different environmental conditions, which enable us to reconstruct genome-scale biomolecular networks (e.g., transcriptional regulatory networks, interactomic networks, and metabolic networks)Knowledge Discovery Handbook: Preprocessing, Mining, and Postprocessing of Biological Data, First Edition. Edited by Mourad Elloumi and Albert Y. Zomaya.

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Calculation of theoretical yields in metabolic networks*

Cited by 9 publications

References 4 publications

Stoichiometric estimates of the biochemical conversion efficiencies in tsetse metabolism

Stoichiometric estimates of the biochemical conversion efficiencies in tsetse metabolism

Elucidating the Importance of Numeracy Skills for Undergraduate Students in Life Sciences Using the Oxygen Requirement in Yeast as an Example

Integration of Metabolic Knowledge for Genome‐Scale Metabolic Reconstruction

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