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Artículos de revistas sobre el tema "Metabolic pathways analysis"

Autor: Grafiati

Publicado: 25 de mayo de 2024

Última modificación: 31 de julio de 2025

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1

Barik, Dr Bibhuti Prasad. "In Silico Observations and Analysis of Metabolic Pathways." International Journal of Scientific Research 2, no. 11 (2012): 44–48. http://dx.doi.org/10.15373/22778179/nov2013/14.

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2

Katz, J. "Mathematical analysis of metabolic pathways." American Journal of Physiology-Endocrinology and Metabolism 252, no. 4 (1987): E571—E572. http://dx.doi.org/10.1152/ajpendo.1987.252.4.e571.

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3

Forst, Christian V., and Klaus Schulten. "Phylogenetic Analysis of Metabolic Pathways." Journal of Molecular Evolution 52, no. 6 (2001): 471–89. http://dx.doi.org/10.1007/s002390010178.

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4

Moreno-Sánchez, Rafael, Emma Saavedra, Sara Rodríguez-Enríquez, and Viridiana Olín-Sandoval. "Metabolic Control Analysis: A Tool for Designing Strategies to Manipulate Metabolic Pathways." Journal of Biomedicine and Biotechnology 2008 (2008): 1–30. http://dx.doi.org/10.1155/2008/597913.

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The traditional experimental approaches used for changing the flux or the concentration of a particular metabolite of a metabolic pathway have been mostly based on the inhibition or over-expression of the presumed rate-limiting step. However, the attempts to manipulate a metabolic pathway by following such approach have proved to be unsuccessful. Metabolic Control Analysis (MCA) establishes how to determine, quantitatively, the degree of control that a given enzyme exerts on flux and on the concentration of metabolites, thus substituting the intuitive, qualitative concept of rate limiting step

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5

Mattei, Gianluca, Zhuohui Gan, Matteo Ramazzotti, Bernhard O. Palsson, and Daniel C. Zielinski. "Differential Expression Analysis Utilizing Condition-Specific Metabolic Pathways." Metabolites 13, no. 11 (2023): 1127. http://dx.doi.org/10.3390/metabo13111127.

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Pathway analysis is ubiquitous in biological data analysis due to the ability to integrate small simultaneous changes in functionally related components. While pathways are often defined based on either manual curation or network topological properties, an attractive alternative is to generate pathways around specific functions, in which metabolism can be defined as the production and consumption of specific metabolites. In this work, we present an algorithm, termed MetPath, that calculates pathways for condition-specific production and consumption of specific metabolites. We demonstrate that

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6

Liao, James C. "Modelling and analysis of metabolic pathways." Current Opinion in Biotechnology 4, no. 2 (1993): 211–16. http://dx.doi.org/10.1016/0958-1669(93)90127-i.

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7

Arias-Méndez, Esteban, Diego Barquero-Morera, and Francisco J. Torres-Rojas. "Low-Cost Algorithms for Metabolic Pathway Pairwise Comparison." Biomimetics 7, no. 1 (2022): 27. http://dx.doi.org/10.3390/biomimetics7010027.

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Metabolic pathways provide key information for achieving a better understanding of life and all its processes; this is useful information for the improvement of medicine, agronomy, pharmacy, and other similar areas. The main analysis tool used to study these pathways is based on pathway comparison, using graph data structures. Metabolic pathway comparison has been defined as a computationally complex task. In a previous work, two new algorithms were introduced to treat the problem of metabolic pathway pairwise comparison. Here we provide an extended analysis with more data and a deeper analysi

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8

Xie, Fuquan, Zhijun Feng, and Beibei Xu. "Metabolic Characteristics of Gut Microbiota and Insomnia: Evidence from a Mendelian Randomization Analysis." Nutrients 16, no. 17 (2024): 2943. http://dx.doi.org/10.3390/nu16172943.

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Insomnia is a common sleep disorder that significantly impacts individuals’ sleep quality and daily life. Recent studies have suggested that gut microbiota may influence sleep through various metabolic pathways. This study aims to explore the causal relationships between the abundance of gut microbiota metabolic pathways and insomnia using Mendelian randomization (MR) analysis. This two-sample MR study used genetic data from the OpenGWAS database (205 gut bacterial pathway abundance) and the FinnGen database (insomnia-related data). We identified single nucleotide polymorphisms (SNPs) associat

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9

Huang, Yan, Rong Chen, Shuci Yang, Ye Chen, and Xiaoying Lü. "The Mechanism of Interaction Between Gold Nanoparticles and Human Dermal Fibroblasts Based on Integrative Analysis of Transcriptomics and Metabolomics Data." Journal of Biomedical Nanotechnology 18, no. 6 (2022): 1562–76. http://dx.doi.org/10.1166/jbn.2022.3365.

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The aim of this paper was to combine transcriptomics and metabolomics to analyze the mechanism of gold nanoparticles (GNPs) on human dermal fibroblasts (HDFs). First, 20-nm GNPs were prepared, and the differentially expressed genes in HDFs were subsequently screened by transcriptome sequencing technology after 4, 8, and 24 h of treatment with GNPs. By comparing the metabolic pathways in which the metabolites obtained in a previous study were involved, the pathways involving both genes and metabolites were filtered, and the differentially expressed genes and metabolites with upstream and downst

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10

Wedmark, Ylva Katarina, Jon Olav Vik, and Ove Øyås. "A hierarchy of metabolite exchanges in metabolic models of microbial species and communities." PLOS Computational Biology 20, no. 9 (2024): e1012472. http://dx.doi.org/10.1371/journal.pcbi.1012472.

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The metabolic network of an organism can be analyzed as a constraint-based model. This analysis can be biased, optimizing an objective such as growth rate, or unbiased, aiming to describe the full feasible space of metabolic fluxes through pathway analysis or random flux sampling. In particular, pathway analysis can decompose the flux space into fundamental and formally defined metabolic pathways. Unbiased methods scale poorly with network size due to combinatorial explosion, but a promising approach to improve scalability is to focus on metabolic subnetworks, e.g., cells’ metabolite exchanges

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11

Mashima, Izumi, Yu-Chieh Liao, Chieh-Hua Lin, et al. "Comparative Pan-Genome Analysis of Oral Veillonella Species." Microorganisms 9, no. 8 (2021): 1775. http://dx.doi.org/10.3390/microorganisms9081775.

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The genus Veillonella is a common and abundant member of the oral microbiome. It includes eight species, V. atypica, V. denticariosi, V. dispar, V. infantium, V. nakazawae, V. parvula, V. rogosae and V. tobetusensis. They possess important metabolic pathways that utilize lactate as an energy source. However, the overall metabolome of these species has not been studied. To further understand the metabolic framework of Veillonella in the human oral microbiome, we conducted a comparative pan-genome analysis of the eight species of oral Veillonella. Analysis of the oral Veillonella pan-genome reve

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12

Rise, Kjersti, May-Britt Tessem, Finn Drabløs, and Morten Beck Rye. "FunHoP analysis reveals upregulation of mitochondrial genes in prostate cancer." PLOS ONE 17, no. 10 (2022): e0275621. http://dx.doi.org/10.1371/journal.pone.0275621.

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Mitochondrial activity in cancer cells has been central to cancer research since Otto Warburg first published his thesis on the topic in 1956. Although Warburg proposed that oxidative phosphorylation in the tricarboxylic acid (TCA) cycle was perturbed in cancer, later research has shown that oxidative phosphorylation is activated in most cancers, including prostate cancer (PCa). However, more detailed knowledge on mitochondrial metabolism and metabolic pathways in cancers is still lacking. In this study we expand our previously developed method for analyzing functional homologous proteins (Fun

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13

Leiser, Scott, Christopher Choi, Ajay Bhat, and Charles Evans. "A Metabolic Stress Response." Innovation in Aging 4, Supplement_1 (2020): 123. http://dx.doi.org/10.1093/geroni/igaa057.404.

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Abstract An organism’s ability to respond to stress is crucial for long-term survival. These stress responses are coordinated by distinct but overlapping pathways, many of which have been found to also regulate longevity in multiple organisms across species. Despite extensive effort, our understanding of these pathways and how they affect aging remains incomplete and thus is a key area of study in Geroscience. Our previous work identified flavin-containing monooxygenase-2 (fmo-2) as a key longevity-promoting gene downstream of at least three longevity promoting pathways, including the hypoxic

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14

Hu, Hejing, Qiuling Li, Lizhen Jiang, Yang Zou, Junchao Duan, and Zhiwei Sun. "Genome-wide transcriptional analysis of silica nanoparticle-induced toxicity in zebrafish embryos." Toxicology Research 5, no. 2 (2016): 609–20. http://dx.doi.org/10.1039/c5tx00383k.

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Silica nanoparticle-induced toxicity in zebrafish embryos affected expression of 2515 genes. Pathway analysis and Signal-net analysis indicated that the gap junction, vascular smooth muscle contraction, and metabolic pathways, apoptosis, the MAPK signaling pathway, the calcium signaling pathway and the JAK-STAT signaling pathway were the most prominent significant pathways in SiNP-induced toxicity in zebrafish embryos.

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15

Siriwan, Wanwisa, Nattachai Vannatim, Somruthai Chaowongdee, et al. "Integrated Proteomic and Metabolomic Analysis of Cassava cv. Kasetsart 50 Infected with Sri Lankan Cassava Mosaic Virus." Agronomy 13, no. 3 (2023): 945. http://dx.doi.org/10.3390/agronomy13030945.

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Cassava mosaic disease (CMD) is a major disease affecting cassava production in Southeast Asia. This study aimed to perform an integrated proteomics and metabolomics analysis of cassava cv. Kasetsart 50 infected with Sri Lankan cassava mosaic virus (SLCMV). Proteomics analyses revealed that 359 proteins were enriched in the plant–pathogen interaction, plant hormone signal transduction, and MAPK signaling pathways. A total of 79 compounds were identified by metabolomics analysis of the healthy and SLCMV-infected cassava plants. Integrated omics analysis revealed that 9 proteins and 5 metabolite

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16

Wang, Xi, Weilan Wu, Jing Liu, et al. "Neurotransmitter Metabolic Disturbance in Methamphetamine Abusers: Focus on Tryptophan and Tyrosine Metabolic Pathways." Toxics 12, no. 12 (2024): 912. https://doi.org/10.3390/toxics12120912.

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Methamphetamine (METH) abuse disrupts the homeostasis of neurotransmitter (NT) metabolism, contributing to a wide range of neurological and psychological disorders. However, the specific effects of METH on NT metabolism, particularly for the tryptophan (TRP) and tyrosine (TYR) metabolic pathways, remain poorly understood. In this study, serum samples from 78 METH abusers and 79 healthy controls were analyzed using Ultra-High-Performance Liquid Chromatography with Tandem Mass Spectrometry (UHPLC-MS/MS). A total of 41 substances, primarily from the TRP and TYR metabolic pathways, were detected a

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17

Thurley, Kevin, Christopher Herbst, Felix Wesener, et al. "Principles for circadian orchestration of metabolic pathways." Proceedings of the National Academy of Sciences 114, no. 7 (2017): 1572–77. http://dx.doi.org/10.1073/pnas.1613103114.

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Circadian rhythms govern multiple aspects of animal metabolism. Transcriptome-, proteome- and metabolome-wide measurements have revealed widespread circadian rhythms in metabolism governed by a cellular genetic oscillator, the circadian core clock. However, it remains unclear if and under which conditions transcriptional rhythms cause rhythms in particular metabolites and metabolic fluxes. Here, we analyzed the circadian orchestration of metabolic pathways by direct measurement of enzyme activities, analysis of transcriptome data, and developing a theoretical method called circadian response a

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18

AY, FERHAT, TAMER KAHVECI, and VALÉRIE DE CRÉCY-LAGARD. "A FAST AND ACCURATE ALGORITHM FOR COMPARATIVE ANALYSIS OF METABOLIC PATHWAYS." Journal of Bioinformatics and Computational Biology 07, no. 03 (2009): 389–428. http://dx.doi.org/10.1142/s0219720009004163.

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Pathways show how different biochemical entities interact with one another to perform vital functions for the survival of an organism. Comparative analysis of pathways is crucial in identifying functional similarities that are difficult to identify by comparing individual entities that build up these pathways. When interacting entities are of single type, the problem of identifying similarities by aligning the pathways can be reduced to graph isomorphism problem. For pathways with varying types of entities such as metabolic pathways, alignment problem is even more challenging. In order to simp

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19

SINGH, SHAILZA, B. K. MALIK, and D. K. SHARMA. "METABOLIC PATHWAY ANALYSIS OFS. PNEUMONIAE: ANIN SILICOAPPROACH TOWARDS DRUG-DESIGN." Journal of Bioinformatics and Computational Biology 05, no. 01 (2007): 135–53. http://dx.doi.org/10.1142/s0219720007002564.

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The emergence of multidrug resistant varieties of Streptococcus pneumoniae (S. pneumoniae) has led to a search for novel drug targets. An in silico comparative analysis of metabolic pathways of the host Homo sapiens (H. sapiens) and the pathogen S. pneumoniae have been performed. Enzymes from the biochemical pathways of S. pneumoniae from the KEGG metabolic pathway database were compared with proteins from the host H. sapiens, by performing a BLASTp search against the non-redundant database restricted to the H. sapiens subset. The e-value threshold cutoff was set to 0.005. Enzymes, which do no

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20

Moiz, Bilal, Jonathan Garcia, Sarah Basehore, et al. "13C Metabolic Flux Analysis Indicates Endothelial Cells Attenuate Metabolic Perturbations by Modulating TCA Activity." Metabolites 11, no. 4 (2021): 226. http://dx.doi.org/10.3390/metabo11040226.

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Disrupted endothelial metabolism is linked to endothelial dysfunction and cardiovascular disease. Targeted metabolic inhibitors are potential therapeutics; however, their systemic impact on endothelial metabolism remains unknown. In this study, we combined stable isotope labeling with 13C metabolic flux analysis (13C MFA) to determine how targeted inhibition of the polyol (fidarestat), pentose phosphate (DHEA), and hexosamine biosynthetic (azaserine) pathways alters endothelial metabolism. Glucose, glutamine, and a four-carbon input to the malate shuttle were important carbon sources in the ba

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21

Lee, Yu Ra, Bark Lynn Lew, Woo Young Sim, Jongki Hong, and Bong Chul Chung. "Alterations in Pattern Baldness According to Sex: Hair Metabolomics Approach." Metabolites 11, no. 3 (2021): 178. http://dx.doi.org/10.3390/metabo11030178.

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Pattern baldness has been associated with the male hormone, dihydrotestosterone. In this study, we tried to determine how the overall metabolic pathways of pattern baldness differ in patients and in normal controls. Our study aimed to identify alterations in hair metabolomic profiles in order to identify possible markers of pattern baldness according to sex. Untargeted metabolomics profiling in pattern baldness patients and control subjects was conducted using ultra-performance liquid chromatography-mass spectrometry. To identify significantly altered metabolic pathways, partial least squares

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22

Sima, Chongyuan, Qifan Zhang, Xiaoli Yu, Bo Yan, and Shulin Zhang. "Metabolic Changes in Zebrafish Larvae Infected with Mycobacterium marinum: A Widely Targeted Metabolomic Analysis." Metabolites 15, no. 7 (2025): 449. https://doi.org/10.3390/metabo15070449.

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Objectives: To explore the metabolic changes in zebrafish larvae after infection with Mycobacterium marinum, this study adopted a widely targeted metabolomic approach to analyze the changes in the overall metabolic profiles of zebrafish larvae infected for 5 days. Methods: Data were collected by liquid chromatography–tandem mass spectrometry (LC-MS/MS). Mass spectrometry data were processed using Analyst 1.6.3 and MultiQuant 3.0.3 software, and multivariate statistical analysis was carried out. The KEGG database, HMDB database, and CHEBI database were used to screen and identify differential m

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23

Brister, Danielle, Brianna A. Werner, Geoffrey Gideon, et al. "Central Nervous System Metabolism in Autism, Epilepsy and Developmental Delays: A Cerebrospinal Fluid Analysis." Metabolites 12, no. 5 (2022): 371. http://dx.doi.org/10.3390/metabo12050371.

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Neurodevelopmental disorders are associated with metabolic pathway imbalances; however, most metabolic measurements are made peripherally, leaving central metabolic disturbances under-investigated. Cerebrospinal fluid obtained intraoperatively from children with autism spectrum disorder (ASD, n = 34), developmental delays (DD, n = 20), and those without known DD/ASD (n = 34) was analyzed using large-scale targeted mass spectrometry. Eighteen also had epilepsy (EPI). Metabolites significantly related to ASD, DD and EPI were identified by linear models and entered into metabolite–metabolite netw

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24

Lundy, Thomas, and Asok K. Sen. "Sign Pattern Analysis of Control Coefficients of Metabolic Pathways." SIAM Journal on Matrix Analysis and Applications 16, no. 3 (1995): 828–42. http://dx.doi.org/10.1137/s0895479892228201.

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25

Shi, Xiang, Lu Zhang, Wei Huang, et al. "Genetic Analyses Identify Human Serum Metabolites Associated With Risk of Gastroesophageal Reflux Disease: A Mendelian Randomization Study." British Journal of Hospital Medicine 86, no. 7 (2025): 1–19. https://doi.org/10.12968/hmed.2025.0067.

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Aims/Background Gastroesophageal reflux disease (GERD) is a widespread upper esophagogastric disease with incompletely understood biological mechanisms. Emerging evidence supports a complex link between GERD and metabolic markers. Therefore, Mendelian randomization (MR), an innovative genomic approach, was used to evaluate the causal impacts of serum metabolites on GERD, aiming to identify novel biomarkers and elucidate underlying metabolic pathways. Methods A two-sample MR framework was employed to examine causal relationships between circulating metabolites and GERD. Genetic instruments for

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26

Chakraborty, Sabuj, Rojina Khatun, Sudeshna Sengupta, and Malavika Bhattacharya. "Decoding Metabolic Pathway: Leveraging Computational Tools for Insight." Computational Biology and Bioinformatics 13, no. 1 (2025): 1–16. https://doi.org/10.11648/j.cbb.20251301.11.

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His chapter introduces us to the role of cellular signaling pathways and their significance in understanding the intricate working of an organism’s functioning, life processes and enable us in deepening of our understanding of many diseases. Through time many relevant pathways has been discovered, we are yet to discover more and even identify missing pieces of existing pathways. Use of novel computational tools, that integrates principles from computer science, mathematics, and biology help us to enhance our understanding of signaling pathways. Its significance lies in its ability to predict p

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27

Klesmith, Justin R., and Timothy A. Whitehead. "High-throughput evaluation of synthetic metabolic pathways." TECHNOLOGY 04, no. 01 (2016): 9–14. http://dx.doi.org/10.1142/s233954781640001x.

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A central challenge in the field of metabolic engineering is the efficient identification of a metabolic pathway genotype that maximizes specific productivity over a robust range of process conditions. Here we review current methods for optimizing specific productivity of metabolic pathways in living cells. New tools for library generation, computational analysis of pathway sequence-flux space, and high-throughput screening and selection techniques are discussed.

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28

DE, RAJAT K., and NAMRATA TOMAR. "MODELING THE OPTIMAL CENTRAL CARBON METABOLIC PATHWAYS UNDER FEEDBACK INHIBITION USING FLUX BALANCE ANALYSIS." Journal of Bioinformatics and Computational Biology 10, no. 06 (2012): 1250019. http://dx.doi.org/10.1142/s0219720012500199.

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Metabolism is a complex process for energy production for cellular activity. It consists of a cascade of reactions that form a highly branched network in which the product of one reaction is the reactant of the next reaction. Metabolic pathways efficiently produce maximal amount of biomass while maintaining a steady-state behavior. The steady-state activity of such biochemical pathways necessarily incorporates feedback inhibition of the enzymes. This observation motivates us to incorporate feedback inhibition for modeling the optimal activity of metabolic pathways using flux balance analysis (

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Chen, Wenbo, Xin Chen, Zhenyu Zhao, et al. "Pan-Cancer Identification of Prognostic-Associated Metabolic Pathways." Biology 12, no. 8 (2023): 1129. http://dx.doi.org/10.3390/biology12081129.

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Metabolic dysregulation has been reported involving in the clinical outcomes of multiple cancers. However, systematical identification of the impact of metabolic pathways on cancer prognosis is still lacking. Here, we performed a pan-cancer analysis of popular metabolic checkpoint genes and pathways with cancer prognosis by integrating information of clinical survival with gene expression and pathway activity in multiple cancer patients. By discarding the effects of age and sex, we revealed extensive and significant associations between the survival of cancer patients and the expression of met

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30

Young, Michael R., and David L. Craft. "Pathway-Informed Classification System (PICS) for Cancer Analysis Using Gene Expression Data." Cancer Informatics 15 (January 2016): CIN.S40088. http://dx.doi.org/10.4137/cin.s40088.

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We introduce Pathway-Informed Classification System (PICS) for classifying cancers based on tumor sample gene expression levels. PICS is a computational method capable of expeditiously elucidating both known and novel biological pathway involvement specific to various cancers and uses that learned pathway information to separate patients into distinct classes. The method clearly separates a pan-cancer dataset by tissue of origin and also sub-classifies individual cancer datasets into distinct survival classes. Gene expression values are collapsed into pathway scores that reveal which biologica

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31

Schuster, Stefan, Luís F. de Figueiredo, and Christoph Kaleta. "Predicting novel pathways in genome-scale metabolic networks." Biochemical Society Transactions 38, no. 5 (2010): 1202–5. http://dx.doi.org/10.1042/bst0381202.

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Elementary-modes analysis has become a well-established theoretical tool in metabolic pathway analysis. It allows one to decompose complex metabolic networks into the smallest functional entities, which can be interpreted as biochemical pathways. This analysis has, in medium-size metabolic networks, led to the successful theoretical prediction of hitherto unknown pathways. For illustration, we discuss the example of the phosphoenolpyruvate-glyoxylate cycle in Escherichia coli. Elementary-modes analysis meets with the problem of combinatorial explosion in the number of pathways with increasing

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32

Agarwal, Divyansh, Tina Bharani, and Somabha Mukherjee. "Abstract 2042: Graph-based pathway analysis of T cell populations in hepatocellular carcinoma reveals novel metabolic regulators of tumor-infiltration lymphocyte activity." Cancer Research 83, no. 7_Supplement (2023): 2042. http://dx.doi.org/10.1158/1538-7445.am2023-2042.

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Abstract With advances in single cell RNA sequencing (scRNAseq), accurate detection of perturbed pathways between conditions or cell types of interest becomes a critical analytical step. The ability to model alterations in a set of genes corresponding of a biological function is particularly useful when comparing cells between healthy and tumor tissues. Yet, few tools exist to detect changes in the multivariate distribution of genes corresponding to a given pathway. We developed a novel, graph-based statistical framework based on optimal matching for testing differential distribution of biolog

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Mitchell, Sabrina L., Chunyu Ma, William K. Scott, et al. "Plasma Metabolomics of Intermediate and Neovascular Age-Related Macular Degeneration Patients." Cells 10, no. 11 (2021): 3141. http://dx.doi.org/10.3390/cells10113141.

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To characterize metabolites and metabolic pathways altered in intermediate and neovascular age-related macular degeneration (IAMD and NVAMD), high resolution untargeted metabolomics was performed via liquid chromatography-mass spectrometry on plasma samples obtained from 91 IAMD patients, 100 NVAMD patients, and 195 controls. Plasma metabolite levels were compared between: AMD patients and controls, IAMD patients and controls, and NVAMD and IAMD patients. Partial least-squares discriminant analysis and linear regression were used to identify discriminatory metabolites. Pathway analysis was per

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34

Golpour, Navid, Rune L. Brautaset, Flora Hui, et al. "Identifying potential key metabolic pathways and biomarkers in glaucoma: a systematic review and meta-analysis." BMJ Open Ophthalmology 10, no. 1 (2025): e002103. https://doi.org/10.1136/bmjophth-2024-002103.

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BackgroundGlaucoma, a leading cause of irreversible blindness worldwide, is characterised by retinal ganglion cell degeneration. Increasing evidence points to metabolic dysfunction, particularly mitochondrial dysfunction, as a contributing factor to glaucomatous neurodegeneration. This systematic review and meta-analysis aimed to identify key metabolic pathways and biomarkers associated with primary open-angle glaucoma (POAG).MethodsA systematic literature search was conducted to identify studies measuring metabolites in plasma and aqueous humour from patients with POAG using metabolomics tech

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35

Haj, Amelia K., Haytham Hasan, and Thomas J. Raife. "Heritability of Protein and Metabolite Biomarkers Associated with COVID-19 Severity: A Metabolomics and Proteomics Analysis." Biomolecules 13, no. 1 (2022): 46. http://dx.doi.org/10.3390/biom13010046.

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Objectives: Prior studies have characterized protein and metabolite changes associated with SARS-CoV-2 infection; we hypothesized that these biomarkers may be part of heritable metabolic pathways in erythrocytes. Methods: Using a twin study of erythrocyte protein and metabolite levels, we describe the heritability of, and correlations among, previously identified biomarkers that correlate with COVID-19 severity. We used gene ontology and pathway enrichment analysis tools to identify pathways and biological processes enriched among these biomarkers. Results: Many COVID-19 biomarkers are highly

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36

Ashida, Yuta, Tomonobu Ozaki, and Takenao Ohkawa. "A Comparative Analysis of Metabolic Pathways Based on Metabolic Steady States." IPSJ Transactions on Bioinformatics 2 (2009): 83–92. http://dx.doi.org/10.2197/ipsjtbio.2.83.

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Fell, David A. "Increasing the flux in metabolic pathways: A metabolic control analysis perspective." Biotechnology and Bioengineering 58, no. 2-3 (1998): 121–24. http://dx.doi.org/10.1002/(sici)1097-0290(19980420)58:2/3<121::aid-bit2>3.0.co;2-n.

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Liu, Wenbin, Anmo Zhou, Ziming Shao, et al. "Genome Annotation of Molting-Related Protein-Coding Genes in Propsilocerus akamusi Reveals Transcriptomic Responses to Heavy Metal Contamination." Insects 16, no. 6 (2025): 636. https://doi.org/10.3390/insects16060636.

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The exoskeleton of insects, known as the cuticle, necessitates regular renewal during molting and metamorphosis, with chitin being its primary structural component. Consequently, the molting and metamorphosis processes in insects are characterized by periodic degradation and synthesis of chitin, which are tightly regulated by juvenile hormone (JH) and 20-hydroxyecdysone (20E). Propsilocerus akamusi, a species that plays a crucial role in freshwater ecosystems, demonstrates remarkable resilience to environmental pollutants, including metallic elements found in industrial waste. In this investig

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39

Smith, Thomas Brendan, Kamlesh Patel, Haydn Munford, et al. "High-Speed Tracer Analysis of Metabolism (HS-TrAM)." Wellcome Open Research 3 (August 22, 2018): 5. http://dx.doi.org/10.12688/wellcomeopenres.13387.2.

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Tracing the fate of stable isotopically-enriched nutrients is a sophisticated method of describing and quantifying the activity of metabolic pathways. Nuclear Magnetic Resonance (NMR) spectroscopy offers high resolution data in terms of resolving metabolic pathway utilisation. Despite this, NMR spectroscopy is under-utilised due to length of time required to collect the data, quantification requiring multiple samples and complicated analysis. Here we present two techniques, quantitative spectral filters and enhancement of the splitting of 13C signals due to homonuclear 13C,13C or heteronuclear

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40

Meyers, Jeremy, Raul Castro-Portuguez, Luis Espejo, and George Sutphin. "Genomic Analysis Of NAD+ Synthesis Pathways Involved In Aging and Cancer." Innovation in Aging 5, Supplement_1 (2021): 665. http://dx.doi.org/10.1093/geroni/igab046.2510.

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Abstract Cancer cells have elevated energy demands to sustain continuous growth and other malignant processes and undergo extensive metabolic reprogramming to meet these demands. One element of this reprogramming in many cancer subtypes is elevated synthesis of nicotinamide adenine dinucleotide (NAD+), a critical co-enzyme that supports energy production through both glycolysis and the TCA cycle. The kynurenine metabolic pathway is the evolutionarily conserved means by which cells produce NAD+ de novo from tryptophan. NAD+ levels drop with age, a contributing factor to many forms of age-relate

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Lu, Heng, Yi Chen, and Linlin Li. "Metabolic Pathway Genes Associated with Susceptibility Genes to Coronary Artery Disease." International Journal of Genomics 2018 (2018): 1–12. http://dx.doi.org/10.1155/2018/9025841.

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Coronary artery disease (CAD) is one of the leading threats to global health. Previous research has proven that metabolic pathway disorders, such as high blood lipids and diabetes, are one of the risk factors that mostly cause CAD. However, the crosstalk between metabolic pathways and CAD was mostly studied on physiology processes by analyzing a single gene function. A canonical correlation analysis was used to identify the metabolic pathways, which were integrated as a unit to coexpress with CAD susceptibility genes, and to resolve additional metabolic factors that are related to CAD. Seven p

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42

Nam, Seungyoon, and Yongmin Lee. "Genome-Scale Metabolic Model Analysis of Metabolic Differences between Lauren Diffuse and Intestinal Subtypes in Gastric Cancer." Cancers 14, no. 9 (2022): 2340. http://dx.doi.org/10.3390/cancers14092340.

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Gastric cancer (GC) is one of the most lethal cancers worldwide; it has a high mortality rate, particularly in East Asia. Recently, genetic events (e.g., mutations and copy number alterations) and molecular signaling associated with histologically different GC subtypes (diffuse and intestinal) have been elucidated. However, metabolic differences among the histological GC subtypes have not been studied systematically. In this study, we utilized transcriptome-based genome-scale metabolic models (GEMs) to identify differential metabolic pathways between Lauren diffuse and intestinal subtypes. We

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Tsoi, Ryan, Feilun Wu, Carolyn Zhang, Sharon Bewick, David Karig, and Lingchong You. "Metabolic division of labor in microbial systems." Proceedings of the National Academy of Sciences 115, no. 10 (2018): 2526–31. http://dx.doi.org/10.1073/pnas.1716888115.

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Metabolic pathways are often engineered in single microbial populations. However, the introduction of heterologous circuits into the host can create a substantial metabolic burden that limits the overall productivity of the system. This limitation could be overcome by metabolic division of labor (DOL), whereby distinct populations perform different steps in a metabolic pathway, reducing the burden each population will experience. While conceptually appealing, the conditions when DOL is advantageous have not been rigorously established. Here, we have analyzed 24 common architectures of metaboli

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44

Ge, Kai, and Zhaoyu Geng. "Proteomic analysis of the liver regulating lipid metabolism in Chaohu ducks using two-dimensional electrophoresis." Open Life Sciences 17, no. 1 (2022): 960–72. http://dx.doi.org/10.1515/biol-2022-0101.

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Abstract In this study, we aimed to characterize the liver protein profile of Chaohu ducks using two-dimensional electrophoresis and proteomics. The livers were quickly collected from 120 healthy, 84-day-old Chaohu ducks. The intramuscular fat (IMF) content of the left pectoralis muscle was determined using the Soxhlet extraction method. The total protein of liver tissues from the high and low IMF groups was extracted for proteomics. Functional enrichment analysis of the differentially expressed proteins (DEPs) was conducted using gene ontology (GO) and kyoto encyclopedia of genes and genomes

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Kan, N. E., Z. V. Khachatryan, V. V. Chagovets, et al. "Analysis of metabolic pathways in intrauterine growth restriction." Biomeditsinskaya Khimiya 66, no. 2 (2020): 174–80. http://dx.doi.org/10.18097/pbmc20206602174.

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Objective was to analyze metabolic pathways based on a study of the metabolomic profile of pregnant women with intrauterine growth restriction. The metabolic profile of pregnant women with fetal growth restriction has been analyzed using liquid chromatography-mass spectrometry. At the second stage pathways were identified using SMPDB and MetaboAnalyst databases to clarify the relationship between metabolites. Biological networks allow to determine the effect of proteins on the metabolic pathways involved in pathogenesis of IUGR and determine the epigenetic mechanisms of its formation.

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Min, Yong, Hong Li, Ying Ge, and Jie Chang. "Metabolic Network Analysis Reveals Human Impact on Urban Nitrogen Cycles." Land 13, no. 8 (2024): 1199. http://dx.doi.org/10.3390/land13081199.

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Human interactions have led to the emergence of a higher complexity of urban metabolic networks; hence, traditional natural- or agriculture-oriented biogeochemical models might not be transferred well to urban environments. Increasingly serious environmental problems require the development of new concepts and models. Here, we propose a basic paradigm for urban–rural complex nitrogen (N) metabolic network reconstruction (NMNR) by introducing new concepts and methodologies from systems biology at the molecular scale, analyzing both local and global structural properties and exploring optimizati

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47

Lei, Jinzhou, Wei Zhang, Fangwei Yu, et al. "Integrated Analysis of Transcriptome and Metabolome Reveals Differential Responses to Alternaria brassicicola Infection in Cabbage (Brassica oleracea var. capitata)." Genes 15, no. 5 (2024): 545. http://dx.doi.org/10.3390/genes15050545.

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Black spot, caused by Alternaria brassicicola (Ab), poses a serious threat to crucifer production, and knowledge of how plants respond to Ab infection is essential for black spot management. In the current study, combined transcriptomic and metabolic analysis was employed to investigate the response to Ab infection in two cabbage (Brassica oleracea var. capitata) genotypes, Bo257 (resistant to Ab) and Bo190 (susceptible to Ab). A total of 1100 and 7490 differentially expressed genes were identified in Bo257 (R_mock vs. R_Ab) and Bo190 (S_mock vs. S_Ab), respectively. Kyoto Encyclopedia of Gene

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48

Sen, A. K. "Application of electrical analogues for control analysis of simple metabolic pathways." Biochemical Journal 272, no. 1 (1990): 65–70. http://dx.doi.org/10.1042/bj2720065.

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I have used electrical analogues for calculating the Flux Control Coefficients of metabolic pathways. An analogue circuit consists of resistances that are connected in series (or parallel) with a voltage (or current) source. In constructing the analogues, each of the enzymes in the pathway is associated with a resistance whose magnitude depends on the Elasticity Coefficients of the enzymes. These circuits can be designed in a heuristic fashion directly from the configuration of the pathway, without the necessity of writing down the governing equations with the use of Summation and Connectivity

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Vadehra, Deepak, Spencer Rosario, Jianmin Wang, et al. "Transcriptional metabolic profiling young onset colorectal cancer (CRC) patients." Journal of Clinical Oncology 41, no. 16_suppl (2023): 3509. http://dx.doi.org/10.1200/jco.2023.41.16_suppl.3509.

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3509 Background: Patients diagnosed with colorectal cancer (CRC) at age < 50 years typically present with more advanced disease, resulting in poor therapeutic response and clinical outcomes. Therefore, there is an unmet need to understand the differences in transcriptional profiles between younger (<50) and older ( > 50) CRC patients. Methods: Using TCGA (n = 397; > 50 = 349; < 50 = 48) and Oncology Research Information Exchange network (ORIEN) CRC datasets (n = 460; > 50 = 364 ; < 50 = 96), patients were separated into younger and older populations. Baseline characteristi

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Li, Xi-Lian, Pei-Jing Shen, Wen-Ping Jiang, Ji-Lun Meng, Hai-Hua Cheng, and Qiang Gao. "Metabonomic Analysis of Macrobrachium rosenbergii with Iron Prawn Syndrome (IPS)." Fishes 8, no. 4 (2023): 196. http://dx.doi.org/10.3390/fishes8040196.

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We previously reported on the comparison of proteomic data between seven tissue types of a novel “iron prawn” species. However, no transcripts or metabolic information are available for this species. We therefore performed shotgun LC–MS/MS metabonomic and RNA-seq analyses of the total protein from “iron prawns”. KEGG analysis revealed that the largest group consisted of a total of 114 KEGG pathway proteins, comparing the “iron prawns” with the normal prawns. A total of 423 peptides, corresponding to metabolic pathways, ABC transporters, starch and sucrose metabolism, insulin resistance/secreti

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