On correlated reaction sets and coupled reaction sets in metabolic networks

2015 ◽  
Vol 13 (04) ◽  
pp. 1571003 ◽  
Author(s):  
Sayed-Amir Marashi ◽  
Zhaleh Hosseini

Two reactions are in the same "correlated reaction set" (or "Co-Set") if their fluxes are linearly correlated. On the other hand, two reactions are "coupled" if nonzero flux through one reaction implies nonzero flux through the other reaction. Flux correlation analysis has been previously used in the analysis of enzyme dysregulation and enzymopathy, while flux coupling analysis has been used to predict co-expression of genes and to model network evolution. The goal of this paper is to emphasize, through a few examples, that these two concepts are inherently different. In other words, except for the case of full coupling, which implies perfect correlation between two fluxes (R2 = 1), there are no constraints on Pearson correlation coefficients (CC) in case of any other type of (un)coupling relations. In other words, Pearson CC can take any value between 0 and 1 in other cases. Furthermore, by analyzing genome-scale metabolic networks, we confirm that there are some examples in real networks of bacteria, yeast and human, which approve that flux coupling and flux correlation cannot be used interchangeably.

2012 ◽  
Vol 13 (1) ◽  
Author(s):  
Abdelhalim Larhlimi ◽  
Laszlo David ◽  
Joachim Selbig ◽  
Alexander Bockmayr

2014 ◽  
Vol 12 (05) ◽  
pp. 1450028 ◽  
Author(s):  
Abolfazl Rezvan ◽  
Sayed-Amir Marashi ◽  
Changiz Eslahchi

A metabolic network model provides a computational framework to study the metabolism of a cell at the system level. Due to their large sizes and complexity, rational decomposition of these networks into subsystems is a strategy to obtain better insight into the metabolic functions. Additionally, decomposing metabolic networks paves the way to use computational methods that will be otherwise very slow when run on the original genome-scale network. In the present study, we propose FCDECOMP decomposition method based on flux coupling relations (FCRs) between pairs of reaction fluxes. This approach utilizes a genetic algorithm (GA) to obtain subsystems that can be analyzed in isolation, i.e. without considering the reactions of the original network in the analysis. Therefore, we propose that our method is useful for discovering biologically meaningful modules in metabolic networks. As a case study, we show that when this method is applied to the metabolic networks of barley seeds and yeast, the modules are in good agreement with the biological compartments of these networks.


2021 ◽  
Vol 51 (6) ◽  
Author(s):  
Tatiana Saraiva Torres ◽  
Luciano Silva Sena ◽  
Alan Oliveira do Ó ◽  
Gleyson Vieira dos Santos ◽  
Artur Oliveira Rocha ◽  
...  

ABSTRACT: The aim of this study was to evaluate the influence of different non-genetic effects on indicator traits for maternal ability in Santa Inês ewes. Data included performance records of 100 lambs (males and females) born from 59 dams, from 2009 to 2012. The analyzed traits were birth weight (BW), weaning weight (WW), average daily gain from birth until weaning (ADGBW), total litter weight at birth (TLWB), and total litter weight at weaning (TLWW). The effects analyzed were the year of birth of the lamb, birth season, dam age at lambing, dam weight at lambing, sex of the lamb, lamb birth type, interaction between sex and birth type, and interaction between sex and birth season. SAS® software (SAS University Edition, USA) was used for calculation of the analysis of variance, means, and Pearson correlation coefficients. With the exception of the birth season, all the other environmental effects evaluated had a significant influence on at least one of the studied traits. The correlation estimates ranged from low to high and were either positive or negative. Birth weight was negatively correlated with the birth type and influenced positively all the other performance traits evaluated. The maternal ability of Santa Inês ewes was more clearly influenced by the age and weight of the dam at lambing, and the lamb birth type.


2020 ◽  
Vol 29 (3) ◽  
pp. 429-435
Author(s):  
Patricia C. Mancini ◽  
Richard S. Tyler ◽  
Hyung Jin Jun ◽  
Tang-Chuan Wang ◽  
Helena Ji ◽  
...  

Purpose The minimum masking level (MML) is the minimum intensity of a stimulus required to just totally mask the tinnitus. Treatments aimed at reducing the tinnitus itself should attempt to measure the magnitude of the tinnitus. The objective of this study was to evaluate the reliability of the MML. Method Sample consisted of 59 tinnitus patients who reported stable tinnitus. We obtained MML measures on two visits, separated by about 2–3 weeks. We used two noise types: speech-shaped noise and high-frequency emphasis noise. We also investigated the relationship between the MML and tinnitus loudness estimates and the Tinnitus Handicap Questionnaire (THQ). Results There were differences across the different noise types. The within-session standard deviation averaged across subjects varied between 1.3 and 1.8 dB. Across the two sessions, the Pearson correlation coefficients, range was r = .84. There was a weak relationship between the dB SL MML and loudness, and between the MML and the THQ. A moderate correlation ( r = .44) was found between the THQ and loudness estimates. Conclusions We conclude that the dB SL MML can be a reliable estimate of tinnitus magnitude, with expected standard deviations in trained subjects of about 1.5 dB. It appears that the dB SL MML and loudness estimates are not closely related.


2016 ◽  
Vol 1 (1) ◽  
pp. 1-15
Author(s):  
Frederich Oscar Lontoh

This research is titled " The influence of sermon, church music and church facilities on the level of attendance”. The purpose of research is to identify and analyze whether sermon, church music and church facilities have influence on the the level of attendance. The target population in this study is a Christian church members who live in the city of Surabaya.. Sample required is equal to 47 respondents. Through sampling stratified Random techniques.These influence was measured using Pearson correlation coefficient and multiple regression analysis, t-test and analysis of variance. Descriptive  analysis  were taken to analyze the level of attendance according to demographic groups.The hypothesis in this study are the sermon, church music and church facilities have positive and significant on the level of attendance. The results showed that collectively, there are positive and significant correlation among the sermon, church music and church facilities on the level of attendance  96,2%. It means that 96,2 % of level of attendance influenced by sermon, church music and church facilities and the other 28,9% by others. All of the variable partially have significant correlation to level of attendance.


2020 ◽  
Vol 4 (1) ◽  
pp. 51-63
Author(s):  
Peter Neuhaus ◽  
Chris Jumonville ◽  
Rachel A. Perry ◽  
Roman Edwards ◽  
Jake L. Martin ◽  
...  

AbstractTo assess the comparative similarity of squat data collected as they wore a robotic exoskeleton, female athletes (n=14) did two exercise bouts spaced 14 days apart. Data from their exoskeleton workout was compared to a session they did with free weights. Each squat workout entailed a four-set, four-repetition paradigm with 60-second rest periods. Sets for each workout involved progressively heavier (22.5, 34, 45.5, 57 kg) loads. The same physiological, perceptual, and exercise performance dependent variables were measured and collected from both workouts. Per dependent variable, Pearson correlation coefficients, t-tests, and Cohen's d effect size compared the degree of similarity between values obtained from the exoskeleton and free weight workouts. Results show peak O2, heart rate, and peak force data produced the least variability. In contrast, far more inter-workout variability was noted for peak velocity, peak power, and electromyography (EMG) values. Overall, an insufficient amount of comparative similarity exists for data collected from both workouts. Due to the limited data similarity, the exoskeleton does not exhibit an acceptable degree of validity. Likely the cause for the limited similarity was due to the brief amount of familiarization subjects had to the exoskeleton prior to actual data collection. A familiarization session that accustomed subjects to squats done with the exoskeleton prior to actual data collection may have considerably improved the validity of data obtained from that device.


Author(s):  
Jan Christoff Visagie ◽  
Michael M. Jones ◽  
Herman L. Linde

The South African workplace is confronted with many leadership challenges, specifically those relating to the employment relationship between subordinates and their supervisors. A high-quality relationship is essential, considering the work-family spillovers employees experience. Limited research has been conducted on the potential positive and negative consequences of the leader-member exchange (LMX) dyadic relationship. In this study, we used a cross-sectional research design, and drew an employee sample (N = 120) from a commuter transport engineering company. A five-point Likert scale was employed and statistical analyses were carried out using the SAS statistical program. We calculated Pearson correlation coefficients and used structural equation modelling to test the proposed conceptual model to indicate possible correlations between the different variables. The main finding of the study was that the nature of the LMX relationship quality in the relevant company appeared to be high and positively related to work-home enrichment but negatively related to work-home conflict and role overload. The article concludes by making a number of suggestions to respond to challenges.


Author(s):  
Ryan M Patrick ◽  
Xing-Qi Huang ◽  
Natalia Dudareva ◽  
Ying Li

Abstract Biosynthesis of secondary metabolites relies on primary metabolic pathways to provide precursors, energy, and cofactors, thus requiring coordinated regulation of primary and secondary metabolic networks. However, to date, it remains largely unknown how this coordination is achieved. Using Petunia hybrida flowers, which emit high levels of phenylpropanoid/benzenoid volatile organic compounds (VOCs), we uncovered genome-wide dynamic deposition of histone H3 lysine 9 acetylation (H3K9ac) during anthesis as an underlying mechanism to coordinate primary and secondary metabolic networks. The observed epigenome reprogramming is accompanied by transcriptional activation at gene loci involved in primary metabolic pathways that provide precursor phenylalanine, as well as secondary metabolic pathways to produce volatile compounds. We also observed transcriptional repression among genes involved in alternative phenylpropanoid branches that compete for metabolic precursors. We show that GNAT family histone acetyltransferase(s) (HATs) are required for the expression of genes involved in VOC biosynthesis and emission, by using chemical inhibitors of HATs, and by knocking down a specific HAT gene, ELP3, through transient RNAi. Together, our study supports that regulatory mechanisms at chromatin level may play an essential role in activating primary and secondary metabolic pathways to regulate VOC synthesis in petunia flowers.


FEBS Open Bio ◽  
2021 ◽  
Author(s):  
You‐Tyun Wang ◽  
Min‐Ru Lin ◽  
Wei‐Chen Chen ◽  
Wu‐Hsiung Wu ◽  
Feng‐Sheng Wang

2021 ◽  
pp. 1-16
Author(s):  
Ibtissem Gasmi ◽  
Mohamed Walid Azizi ◽  
Hassina Seridi-Bouchelaghem ◽  
Nabiha Azizi ◽  
Samir Brahim Belhaouari

Context-Aware Recommender System (CARS) suggests more relevant services by adapting them to the user’s specific context situation. Nevertheless, the use of many contextual factors can increase data sparsity while few context parameters fail to introduce the contextual effects in recommendations. Moreover, several CARSs are based on similarity algorithms, such as cosine and Pearson correlation coefficients. These methods are not very effective in the sparse datasets. This paper presents a context-aware model to integrate contextual factors into prediction process when there are insufficient co-rated items. The proposed algorithm uses Latent Dirichlet Allocation (LDA) to learn the latent interests of users from the textual descriptions of items. Then, it integrates both the explicit contextual factors and their degree of importance in the prediction process by introducing a weighting function. Indeed, the PSO algorithm is employed to learn and optimize weights of these features. The results on the Movielens 1 M dataset show that the proposed model can achieve an F-measure of 45.51% with precision as 68.64%. Furthermore, the enhancement in MAE and RMSE can respectively reach 41.63% and 39.69% compared with the state-of-the-art techniques.


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