Relevant bibliographies by topics / Metabolomics

Academic literature on the topic 'Metabolomics'

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Published: 4 June 2021
Last updated: 31 August 2024

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Journal articles on the topic "Metabolomics"

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Pann, Patrick, Martin Hrabě de Angelis, Cornelia Prehn, and Jerzy Adamski. "Mouse Age Matters: How Age Affects the Murine Plasma Metabolome." Metabolites 10, no. 11 (November 19, 2020): 472. http://dx.doi.org/10.3390/metabo10110472.

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A large part of metabolomics research relies on experiments involving mouse models, which are usually 6 to 20 weeks of age. However, in this age range mice undergo dramatic developmental changes. Even small age differences may lead to different metabolomes, which in turn could increase inter-sample variability and impair the reproducibility and comparability of metabolomics results. In order to learn more about the variability of the murine plasma metabolome, we analyzed male and female C57BL/6J, C57BL/6NTac, 129S1/SvImJ, and C3HeB/FeJ mice at 6, 10, 14, and 20 weeks of age, using targeted metabolomics (BIOCRATES AbsoluteIDQ™ p150 Kit). Our analysis revealed high variability of the murine plasma metabolome during adolescence and early adulthood. A general age range with minimal variability, and thus a stable metabolome, could not be identified. Age-related metabolomic changes as well as the metabolite profiles at specific ages differed markedly between mouse strains. This observation illustrates the fact that the developmental timing in mice is strain specific. We therefore stress the importance of deliberate strain choice, as well as consistency and precise documentation of animal age, in metabolomics studies.
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Ivanova, Lada, Oscar D. Rangel-Huerta, Haitham Tartor, Maria K. Dahle, Silvio Uhlig, and Christiane Kruse Fæste. "Metabolomics and Multi-Omics Determination of Potential Plasma Biomarkers in PRV-1-Infected Atlantic Salmon." Metabolites 14, no. 7 (July 2, 2024): 375. http://dx.doi.org/10.3390/metabo14070375.

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Metabolomic analysis has been explored to search for disease biomarkers in humans for some time. The application to animal species, including fish, however, is still at the beginning. In the present study, we have used targeted and untargeted metabolomics to identify metabolites in the plasma of Atlantic salmon (Salmo salar) challenged with Piscine orthoreovirus (PRV-1), aiming to find metabolites associated with the progression of PRV-1 infection into heart and skeletal muscle inflammation (HSMI). The metabolomes of control and PRV-1-infected salmon were compared at three time points during disease development by employing different biostatistical approaches. Targeted metabolomics resulted in the determination of affected metabolites and metabolic pathways, revealing a substantial impact of PRV-1 infection on lipid homeostasis, especially on several (lyso)phosphatidylcholines, ceramides, and triglycerides. Untargeted metabolomics showed a clear separation of the treatment groups at later study time points, mainly due to effects on lipid metabolism pathways. In a subsequent multi-omics approach, we combined both metabolomics datasets with previously reported proteomics data generated from the same salmon plasma samples. Data processing with DIABLO software resulted in the identification of significant metabolites and proteins that were representative of the HSMI development in the salmon.
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Zelentsova, Ekaterina A., Sofia S. Mariasina, Vadim V. Yanshole, Lyudmila V. Yanshole, Nataliya A. Osik, Kirill A. Sharshov, and Yuri P. Tsentalovich. "Quantitative Metabolomic Dataset of Avian Eye Lenses." Data 8, no. 8 (July 31, 2023): 125. http://dx.doi.org/10.3390/data8080125.

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Metabolomics is a powerful set of methods that uses analytical techniques to identify and quantify metabolites in biological samples, providing a snapshot of the metabolic state of a biological system. In medicine, metabolomics may help to reveal the molecular basis of a disease, make a diagnosis, and monitor treatment responses, while in agriculture, it can improve crop yields and plant breeding. However, animal metabolomics faces several challenges due to the complexity and diversity of animal metabolomes, the lack of standardized protocols, and the difficulty in interpreting metabolomic data. The current dataset includes quantitative metabolomic profiles of eye lenses from 26 bird species (111 specimens) that can aid researchers in developing new experiments, mathematical models, and integrating with other “-omics” data. The dataset includes raw 1H NMR spectra, protocols for sample preparation, and data preprocessing, with the final table containing information on the abundance of 89 reliably identified and quantified metabolites. The dataset is quantitative, making it relevant for supplementing with new specimens or comparison groups, followed by data mining and expected new interpretations. The data were obtained using the bird specimens collected in compliance with ethical standards and revealed potential differences in metabolic pathways due to phylogenetic differences or environmental exposure.
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Lankadurai, Brian P., Edward G. Nagato, and Myrna J. Simpson. "Environmental metabolomics: an emerging approach to study organism responses to environmental stressors." Environmental Reviews 21, no. 3 (September 2013): 180–205. http://dx.doi.org/10.1139/er-2013-0011.

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Metabolomics is the analysis of endogenous and exogenous low molecular mass metabolites within a cell, tissue, or biofluid of an organism in response to an external stressor. The sub-discipline of environmental metabolomics is the application of metabolomic techniques to analyze the interactions of organisms with their environment. There has been a rapid growth in environmental metabolomics over the past decade. This growth can be attributed to the comprehensive and rapid nature of nontargeted metabolomics and the ability to generate hypotheses involving complex environmental stressors, especially when the mode of action is unknown. Using a wide variety of model organisms, metabolomic studies have detected stress from abiotic factors such as xenobiotic exposure and temperature shifts as well as biotic stressors such as herbivory and competition. Nuclear magnetic resonance (NMR)-based metabolomics has been the dominant analytical platform used for environmental metabolomics studies, owing to its nonselectivity and ease of sample preparation. However, the number of mass spectrometry (MS)-based metabolomic studies is also increasing rapidly, owing to its high sensitivity for the detection of trace levels of metabolites. In this review, we provide an overview of the general experimental design, extraction methods, analytical instrumentation, and statistical methods used in environmental metabolomics. We then highlight some of the recent studies that have used metabolomics to elucidate hitherto unknown biochemical modes of actions of various environmental stressors to both terrestrial and aquatic organisms, as well as identify potential metabolite shifts as early bioindicators of these stressors. Through this, we emphasize the immense potential and versatility of environmental metabolomics as a routine tool for characterizing the responses of organisms to numerous types of environmental stressors.
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Sebastiani, Paola, and Nalini Raghavachari. "METABOLOMICS OF LONGEVITY AND LIFESPAN." Innovation in Aging 7, Supplement_1 (December 1, 2023): 631. http://dx.doi.org/10.1093/geroni/igad104.2056.

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Abstract Serum metabolomics has been an important source of biomarkers of aging and longevity for years. This symposium will bring together investigators from large studies of human longevity to provide an overview of recent discoveries on serum metabolomics of aging and extreme human longevity, their connections to genetic variations, and highlight the challenges of correlating metabolomic profiles of aging in human studies and across multiple species. Dr. Sebastiani will describe results from analyses of serum metabolomics of participants enrolled in the Long Life Family Study, highlight similarities and differences between metabolomic profiles of old age and extreme old age, and some connections with genetics of extreme human longevity. Dr. Rappaport will connect specific variations of the APOE alleles to metabolomic profiles and describe a possible role of bioenergetics pathways in mediating the effect of APOE to longevity and resistance to Alzheimer’s disease. Dr. Monti will expand the characterization of metabolomics of aging and extreme human longevity in a large metabolomic study of very old centenarians by using traditional statistical analyses and novel machine learning techniques. His analysis identifies rich signatures of aging and longevity that include well known metabolites and point to bile acids and several classes of steroids as important marker of longevity. Analytical innovations will be taken further by Dr. Schork who will introduce a novel approach based on distance of profiles to analyze multiple metabolites simultaneously and show the value of this approach to analyze metabolomic profiles of maximum lifespan across multiple species. This is a Geroscience Interest Group Sponsored Symposium.
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Yanagihara, M., F. Nakajima, and T. Tobino. "Metabolomic responses of an estuarine benthic amphipod to heavy metals at urban-runoff concentrations." Water Science and Technology 78, no. 11 (December 20, 2018): 2349–54. http://dx.doi.org/10.2166/wst.2018.518.

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Abstract Heavy metals released from urban areas have toxic effects on aquatic organisms. Heavy metals in aquatic environments exist in various forms and methods designed to assess their effects need to consider their bioavailability. This study aimed to explore biomarkers in an estuarine amphipod, Grandidierella japonica, for exposure to heavy metals using metabolomics. We exposed G. japonica to different heavy metals and analyzed their metabolomes using high-resolution mass spectrometry. Partial least squares discriminant analysis (PLS-DA) was used to extract biomarkers of exposure for each heavy metal. As a result, three models were built to predict discrimination based on metabolomic profiles, and 70, 106, and 168 metabolites were extracted as biomarkers for exposure to Cu, Zn, and Cd, respectively. Our results suggest that PLS-DA was effective in extracting biomarkers, and this study demonstrated the usefulness of metabolomics as biomarkers.
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Brennan, Lorraine. "Session 2: Personalised nutrition Metabolomic applications in nutritional research." Proceedings of the Nutrition Society 67, no. 4 (October 10, 2008): 404–8. http://dx.doi.org/10.1017/s0029665108008719.

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Metabolomics aims to profile all small molecules that are present in biological samples such as biofluids, tissue extracts and culture media. Combining the data obtained with multivariate data analysis tools allows the exploration of changes induced by a biological treatment or changes resulting from phenotype. Recently, there has been a large increase in interest in using metabolomics in nutritional research and because of the intimate relationship between nutrients and metabolism there exists great potential for the use of metabolomics within nutritional research. However, for metabolomics to reach its full potential within this field it is also important to be realistic about the challenges that are faced. Examples of such challenges include the necessity to have a clear understanding of the causes of variation in human metabolomic profiles, the effects of the gut microflora on the metabolomic profile and the interaction of the gut microflora with the host's metabolism. A further challenge that is particularly relevant for human nutritional research is the difficulty associated with biological interpretation of the data. Notwithstanding these and other challenges, several examples of successful applications to nutritional research exist. The link between the human metabolic phenotype, as characterised by metabolomic profiles, and dietary preferences proposes the potential role of metabolomics in personalised nutrition.
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Wishart, David S., Leo L. Cheng, Valérie Copié, Arthur S. Edison, Hamid R. Eghbalnia, Jeffrey C. Hoch, Goncalo J. Gouveia, et al. "NMR and Metabolomics—A Roadmap for the Future." Metabolites 12, no. 8 (July 23, 2022): 678. http://dx.doi.org/10.3390/metabo12080678.

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Metabolomics investigates global metabolic alterations associated with chemical, biological, physiological, or pathological processes. These metabolic changes are measured with various analytical platforms including liquid chromatography-mass spectrometry (LC-MS), gas chromatography-mass spectrometry (GC-MS) and nuclear magnetic resonance spectroscopy (NMR). While LC-MS methods are becoming increasingly popular in the field of metabolomics (accounting for more than 70% of published metabolomics studies to date), there are considerable benefits and advantages to NMR-based methods for metabolomic studies. In fact, according to PubMed, more than 926 papers on NMR-based metabolomics were published in 2021—the most ever published in a given year. This suggests that NMR-based metabolomics continues to grow and has plenty to offer to the scientific community. This perspective outlines the growing applications of NMR in metabolomics, highlights several recent advances in NMR technologies for metabolomics, and provides a roadmap for future advancements.
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Liu, Rui, Zheng-Xue Bao, Pei-Ji Zhao, and Guo-Hong Li. "Advances in the Study of Metabolomics and Metabolites in Some Species Interactions." Molecules 26, no. 11 (May 31, 2021): 3311. http://dx.doi.org/10.3390/molecules26113311.

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In the natural environment, interactions between species are a common natural phenomena. The mechanisms of interaction between different species are mainly studied using genomic, transcriptomic, proteomic, and metabolomic techniques. Metabolomics is a crucial part of system biology and is based on precision instrument analysis. In the last decade, the emerging field of metabolomics has received extensive attention. Metabolomics not only provides a qualitative and quantitative method for studying the mechanisms of interactions between different species, but also helps clarify the mechanisms of defense between the host and pathogen, and to explore new metabolites with various biological activities. This review focuses on the methods and progress of interspecies metabolomics. Additionally, the prospects and challenges of interspecies metabolomics are discussed.
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Brennan, Lorraine. "Metabolomics in nutrition research: current status and perspectives." Biochemical Society Transactions 41, no. 2 (March 21, 2013): 670–73. http://dx.doi.org/10.1042/bst20120350.

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Metabolomics is the study of metabolites present in biological samples such as biofluids, tissue/cellular extracts and culture media. Combining metabolomic data with multivariate data analysis tools allows us to study alterations in metabolic pathways following different perturbations. Examples of perturbations can be disease state, drug or nutritional interventions with successful applications in the fields of drug toxicology, biomarker development and nutrition research. Application of metabolomics to nutrition research is increasing and applications range from assessing novel biomarkers of dietary intake to application of metabolomics in intervention studies. The present review highlights the use of metabolomics in nutrition research.
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Dissertations / Theses on the topic "Metabolomics"

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Norris, Teresa Emilea. "Metabolomics /." Electronic version (PDF), 2006. http://dl.uncw.edu/etd/2006/norrist/teresanorris.pdf.

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Singmann, Paula. "Metabolomics and aging." Diss., Ludwig-Maximilians-Universität München, 2015. http://nbn-resolving.de/urn:nbn:de:bvb:19-183836.

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As life expectancy has risen steadily over the last years and diseasefree aging is more and more challenging, understanding the complexity of age and aging is of great importance. Metabolomics is one of the novel approaches in systems biology with high potential to deliver answers to these questions. However, only a few metabolic studies based on large samples are available so far. In this thesis, I present results from two population-based studies, the German KORA Follow-Up 4 (KORA F4) study as a discovery cohort with a sample of 1,038 female and 1,124 male healthy participants (32–81 years) and 724 healthy females from UK Adult Twin Registry (TwinsUK) as replication. Targeted metabolomics of fasting serum samples with flow injection analysis coupled with tandem mass spectrometry (FIA-MS/MS) positively quantified 131 metabolites after stringent quality control. Among these, 71 and 34 metabolites were significantly associated with age in females and males, respectively, after adjustment for body mass index (BMI), which is highly correlated (r=0.9) with age. These results indicate that metabolic profiles are age dependent and sex specific. Then, a set of the 12 most age-discriminative, independent metabolites was identified in women with an approach based on random forest and stepwise variable selection. This set showed highly significant differences between subjects aged 32–51 years and 52–77 (p-values range 1.3E-09 – 1.9E-46, significance threshold p=0.004). Ten out of these 12 metabolites replicated in unrelated females from the TwinsUK study, including five metabolites the concentrations of which increased with age (C12:1, C18:1, sphingomyelin (SM) C16:1, SM C18:1 and phosphatidylcholine (PC) aa C28:1), while histidine decreased gradually. Three glycerophospholipids (PC ae C42:4, PC ae C42:5, PC ae C44:4) showed declines around the age of 51 years. Meta-analysis of both studies gave virtually the same results as KORA alone. These observations might reflect many different processes of aging such as incomplete mitochondrial fatty acid oxidation, counteracting oxidative stress, and changes in vascular functions. The identification of these ten age-related metabolites should help better understand aging pathways and networks and with —more discoveries in the future— eventually help enhance healthy aging and longevity.
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Csombordi, Rajmund. "Metabolomics database resolver." Thesis, Uppsala universitet, Institutionen för biologisk grundutbildning, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-417525.

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Metabolomics is a rising field combining bioinformatics and cheminformatics together. A major component of research is having a reliable data source, which usually comes in the form of metabolomic databases. This paper documents arising issues revolving categorizing metabolome compounds within databases, and a possible solution in the form of an R package that is capable of matching up various metabolome identifiers that originate from various metabolome databases. Then, by using this package we reflect on the average coverage of external reference between metabolome databases to highlight the lack of a universal compound primary identifier.

The thesis presentation was held over Zoom due to the recent COVID19 pandemic.

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Kapoor, Sabrina Reenu. "Metabolomics of inflammatory arthritis." Thesis, University of Birmingham, 2014. http://etheses.bham.ac.uk//id/eprint/5251/.

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Background Rheumatoid arthritis (RA) is associated with both local and systemic inflammation which influences the function of the whole body as well as local tissues in the joints. Significant consequences of this are changes in metabolism. Hence, we hypothesised that chronic inflammation alters metabolism and that the metabolic profile of an individual patient with early inflammatory arthritis predicts the subsequent course of disease. Furthermore, we suggested that these metabolic changes would identify biomarkers of response to treatment in inflammatory arthritis and provide novel insights into disease mechanisms. Methods Using NMR spectroscopy of serum, urine and synovial fibroblasts we derived metabolic profiles and subjected these to multi-parameter analyses to identify metabolic differences associated with inflammation. Results We were able to predict outcome in patients with early arthritis using material derived from cultured synovial fibroblasts but were unable to do so using serum. There was a significant association between CRP levels in the patients’ serum and the metabolic profile of their synovial fibroblasts and their serum. There was also a significant association between the metabolomic fingerprint of synovial fibroblasts and the fibroblasts’ IL6 production. We found differences in metabolites between urine samples of RA and psoriatic arthritis (PsA) patients and were able to predict responses to anti-TNF therapy in patients with RA. Discussion Our results demonstrate that underlying inflammatory processes drive significant changes in metabolism that can be measured in the peripheral blood, synovial fibroblasts and urine samples in patients with inflammatory arthritis.
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Urbanski, John Paul. "Microfluidic tools for metabolomics." Thesis, Massachusetts Institute of Technology, 2008. http://hdl.handle.net/1721.1/46495.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2008.
Includes bibliographical references (p. 153-160).
A primary challenge in embryology is to understand the factors that govern the development of preimplantation (PI) embryos and how these factors relate to embryo viability in the field of in vitro fertilization (IVF). This is particularly important as clinical policy moving towards single embryo transfer (SET) has gained awareness to manage unprecedented numbers of multiple births, such as twins and triplets, resulting from artificial reproductive techniques. Conditions that correlate with developmental potential of candidate embryos are disputed in the field, however, as the requisite data is difficult to obtain.The metabolic profiles of embryos during in vitro culture have been suggested as a key indicator of developmental potential, and approaches have been clinically implemented to select transfer candidates which make the most efficient use of nutrients. Existing microdroplet analysis techniques are accurate and suitable for non-invasive assessment of single embryos. Unfortunately, the process of determining metabolite levels in nanoliters of culture media through fluorometric assays is low-throughput and requires specialized expertise, hindering widespread clinical use of these methods. The goal of this thesis is to develop microfluidics-based approaches for improving metabolic analysis of PI embryos and mammalian cells. This challenge necessitates two competencies: methods for automating chemical assays and methods for supporting cell cultures, which can be integrated with analysis. Contributions include a standalone platform for determining the metabolite use of single embryos. Profiles may be acquired automatically, which reduces significant technician hours and improves repeatability. Techniques are developed for performing embryo culture in the smallest culture volumes to date in microfabricated environments. Microfluidic approaches have enabled culture that outperforms the current state of art approach based on cell count measurements.
(cont.) An integrated system is introduced, merging analysis and culture competencies to perform metabolic profiling of separate cultures of mammalian cells in parallel. Finally, new paradigms in microfluidic design are presented based on the concept of vertically integrated architectures, suitable for overcoming density limitations of microfluidic assays. A scalable analysis platform for refining embryo selection has been long warranted and would enable pursuit of the difficult questions relating metabolism and embryo viability as the clinical movement towards SET continues.
by John Paul Urbanski.
Ph.D.
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Muncey, Harriet Jane. "Statistical methods in metabolomics." Thesis, Imperial College London, 2014. http://hdl.handle.net/10044/1/24877.

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Metabolomics lies at the fulcrum of the system biology 'omics'. Metabolic profiling offers researchers new insight into genetic and environmental interactions, responses to pathophysi- ological stimuli and novel biomarker discovery. Metabolomics lacks the simplicity of a single data capturing technique; instead, increasingly sophisticated multivariate statistical techniques are required to tease out useful metabolic features from various complex datasets. In this work, two major metabolomics methods are examined: Nuclear Magnetic Resonance (NMR) Spec- troscopy and Liquid Chromatography-Mass Spectrometry (LC-MS). MetAssimulo, an 1H-NMR metabolic-profile simulator, was developed in part by this author and is described in the Chap- ter 2. Peak positional variation is a phenomenon occurring in NMR spectra that complicates metabolomic analysis so Chapter 3 focuses on modelling the effect of pH on peak position. Analysis of LC-MS data is somewhat more complex given its 2-D structure, so I review existing pre-processing and feature detection techniques in Chapter 4 and then attempt to tackle the issue from a Bayesian viewpoint. A Bayesian Partition Model is developed to distinguish chro- matographic peaks representing useful features from chemical and instrumental interference and noise. Another of the LC-MS pre-processing problems, data binning, is also explored as part of H-MS: a pre-processing algorithm incorporating wavelet smoothing and novel Gaussian and Exponentially Modified Gaussian peak detection. The performance of H-MS is compared alongside two existing pre-processing packages: apLC-MS and XCMS.
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Zubair, Mohammed. "Metabolomics in Alzheimer's disease." Thesis, University of Manchester, 2013. https://www.research.manchester.ac.uk/portal/en/theses/metabolomics-in-alzheimers-disease(0872757b-d25a-4c43-bd52-915d4cad21c6).html.

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Metabolites are a potentially useful source of detecting and identifying disease specific biomarkers. This thesis investigates the possibility of using metabolomics applications to detect Alzheimer’s disease associated metabolite peaks in patients and to detect longitudinal changes of the disease. Serum samples and clinical data were collected from 60 healthy controls and 60 Alzheimer’s disease patients (60 at baseline and 60 at 12 month follow-up). The metabolic fingerprinting of serum samples using the FT-IR lacked discriminatory power to discriminate Alzheimer’s disease and non-disease samples due to the similar magnitude of biological and analytical variation. The metabolic profiling of serum samples using the GC-ToF-MS did not reveal any significantly altered metabolite peaks between the Alzheimer’s disease and non-disease groups. Metabolic profiling of serum samples using the UPLC-LTQ/Orbitrap-MS operated in the positive ionisation mode did not reveal any significantly altered metabolite peaks between the disease and non-disease groups. Up to twelve metabolite peaks were significantly altered in the Alzheimer’s disease baseline and follow-up samples, indicating a potential association with disease progression. Metabolic profiling of serum samples using the UPLC-LTQ/Orbitrap-MS operated in the negative ionisation mode did not reveal any significantly altered metabolite peaks between Alzheimer’s disease and non-disease groups. Three metabolite peaks were significantly altered in the Alzheimer’s disease baseline and follow-up samples, indicating a potential association with disease progression. Metabolic profiling of serum samples with the UPLC-LTQ/Orbitrap-MS may potentially be used to detect disease and disease progression associated metabolite peaks. The metabolite peaks require identification followed by a validation experiment.
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McKeating, Daniel R. "Elemental Metabolomics in Pregnancy." Thesis, Griffith University, 2021. http://hdl.handle.net/10072/403231.

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Nutrition is fundamentally important for human health and development; in particular, an adequate supply of macronutrients such as carbohydrates, lipids and proteins as well as specific elements in the form of vitamins and minerals. An insufficient intake of macronutrients or micronutrients leads to poor metabolism and physiological changes associated with a variety of negative health outcomes. Maternal nutrition is perhaps the most important determinant in foetal development in all mammalian species including humans. Additionally, nutrition in pregnancy can have long term effects on the developing infant and has been associated with development of chronic disease later in life. Changes in micronutrient status have been associated with gestational complications such as gestational diabetes mellitus (GDM), preeclampsia (PE), foetal growth restriction (FGR), and preterm birth. Pregnancy disorders such as these are poorly understood despite extensive research, and novel research into this field is desperately required. Recent advancements in technology have allowed the simultaneous measurement of large numbers of elements and metabolites. Currently, we only know how a handful of elements affect pregnancy outcomes, even though many are likely to be essential to human development. This research aimed to determine the elemental nutrition status of pregnant woman and correlate this with (1) weeks gestation, (2) pregnancy health and (3) mechanisms that may contribute to disease, with the ultimate goal of using these values to determine gestational outcomes. This was to be conducted through series of cohort analysis, providing detailed baseline information on micronutrient levels in non-pregnant and pregnant Australians, to then determine if aberrant changes in nutrition are present, and how this may contribute to any disease state. It was critical to establish a means of multi-elemental analysis on ICP-MS that was reproducible and conformed to rigorous quality control standards, ensuring the validity of measurements. This was done through the use of placental cord blood plasma, and in collaboration with an externally accredited laboratory for elemental measurements, ensuring the laboratory facilities and ICP-MS methodologies in place at Griffith University are comparable to a nationally accredited analytical facility. For post method validation, elements within a healthy population had to be determined, to then discern what can be considered abnormal. Elemental reference ranges were established in healthy non-pregnant donors attending the Red Cross Blood Bank (Queensland Red Cross Blood Service). Generally, the levels of elements were comparable to other countries and within published reference ranges. Age was associated with increases in Fe, Se, Cd, Cs, and Pb; whilst Cu, I, and Tl decreased. Sex specific differences included higher levels of Mg, K, Fe, Zn, Se, Rb, Cs, and Pb in males; whilst females had higher concentrations of Co, Cu, As, and Cd. What was interesting, was the varied concentrations of some elements between some regions within the same country, a trend that would be repeated across different studies in this thesis. Having measured the concentrations of elements in a non-pregnant population, it was essential to quantify elements in pregnant women across gestation for comparison and to determine what may be considered normal for gestation. Due to the constant growth and change that is associated with pregnancy, non-pregnant, 18-, 28-, and 36-week pregnant women were tested. There were no signs of elemental deficiencies, or over nutrition in either the non-pregnant or pregnant samples in these studies; nor was there any evidence of pollutants, contaminants, or abnormal levels of heavy metals. It was established that the changes that occur across gestation are extensive, with concentrations varying throughout gestation. However, it appears that there are a number of key factors that may influence these gestational concentrations that need to be considered, namely environmental exposures and collection methods. Further this project then highlighted changes of elements that occurred across gestation, and in pregnancy outcomes such as PE, GDM, FGR, and preterm birth. It assessed the use of elements as a means of predicting gestational outcomes at 18 and 36-weeks, indicating that earlier gestation measurements may provide a better means of discrimination, though validation is required in order to confirm these results. This thesis also evaluated small molecule metabolites and their ability to characterise and differentiate, non-pregnant, healthy pregnant, and poor gestational outcomes, noting significantly better results than elemental analysis. Specifically, in discrimination capabilities with data analysis models, small molecule metabolites outperformed the models constructed based on elements. Although further validation is required before these methods could be applied clinically. Knowledge of the influence of region, collections methods, and time of sample collection were also highlighted through cohorts from across Australia. This thesis proposes the use of a standard operating procedure for elemental and metabolic analysis to ensure the consistency of measurements, aiming to minimise preventable variance in the future.
Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Medical Science
Griffith Health
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Moutloatse, Gontse Panache. "Metabolomics of bilharziasis / Moutloatse G.P." Thesis, North-West University, 2012. http://hdl.handle.net/10394/8206.

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Bilharziasis, a disease that is a major health problem in tropical and subtropical countries, is caused by worms of the genus Schistosoma. The main disease–causing species are S. haematobium, S. mansoni and S. japonicum. Bilharziasis is endemic in South Africa, mostly located in the north–east and covers one quarter of the country, with S. haematobium being the most common species. In this investigation we investigated the schistosome–induced changes in human hosts. We systematically investigated the dynamic metabolic profile of humans infected with S. haematobium using an untargeted gas chromatography?mass spectrometry (GC–MS) metabolomics approach, including univariate and multivariate data analysis. The analysis of host urinary composition is a well suited approach to understand the holistic metabolic responses to infections, since metabolomics is a branch of science concerned with the metabolite composition of biological systems and its dynamic response to both endogenous (i.e. physiology and development) and exogenous (i.e. environmental factors and xenobiotics) stimuli. As a holistic approach, metabonomics detects, quantifies and catalogues metabolic processes of an integrated biological system. In this investigation we selected the organic acid component of the metabolome for the metabolic profiling. Organic acids were determined from urine samples obtained from humans infected with S. haematobium and a control group of non–infected humans. These metabolites were quantified and identified using an automated mass spectral deconvolution and identification system (AMDIS) from which complex two–dimensional data–matrix sets were created, including assessment of the repeatability in generating a metabolomics matrix. Data matrices were analyzed by principal component and partial least square discriminant analyses (PCA and PLS–DA) to investigate which perturbations existed between the two experimental groups. The biochemical interpretation of the information from these analyses indicated that the main biochemical effects of a S. haematobium infection in humans consisted of reduced energy metabolism, liver–function disturbances and perturbations in the gut microbial population common to infections caused by other schistosoma species. Alterations of metabolites of the phenylalanine–tyrosine pathway, including aspects of catecholamine metabolism seems to be novel to a S. haematobium ii infection and hasn’t been reported in current literature. Finally, proposals were formulated for future investigations on S. haematobium infection.
Thesis (MSc (Biochemistry))--North-West University, Potchefstroom Campus, 2012.
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Garg, Ramandeep. "NMR metabolomics in nutrition research." Thesis, Ulster University, 2013. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.646846.

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Metabolomics provides an untargeted strategy, which has been used to evaluate the effect of dietary components on human metabolism. Epidemiological evidence indicates that increased consumption of wholegrain foods is positively associated with decreased prevalence of chronic diseases. The aim of the current work was to evaluate the application of NMR metabolomics in nutrition research, using urine and plasma samples from two short-term (postprandial) studies that evaluated responses in men and women to minimally processed wheat bran and aleurone meals, and aleurone processed into bread. The first investigations assessed the application of NMR metabolomics to assess urinary responses while the later investigations assess plasma responses in men and women consuming single meals of minimally processed wheat bran and aleurone. Results showed that there was discrimination between the urinary metabolite profiles at both one and two hours after the consumption of aleurone and bran meals compared to control meal, while there was discrimination after the consumption of aleurone meal compared to the control meal only at one hour in the plasma metabolite profiles. However, there was no clear discrimination between the aleurone and bran meals. The final investigations, which assessed the urinary responses in men and women consuming single meals of aleurone fraction incorporated into bread, showed that there was discrimination between the urinary metabolite profiles only at two hours after the control bread compared to aleurone bread. Furthermore, there were differences in urinary and plasma metabolite profiles between females and males after meal consumption throughout suggesting that gender-related differences may be important, and may need to be taken into account in metabolomics studies that assess postprandial effects. This is the first human metabolomics study exploring the gender-related differences of wholegrain meal consumption. Overall, the results indicated that metabolomics has been successful in articulating the effects of wholegrains and gender-related differences.
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Books on the topic "Metabolomics"

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Wehrens, Ron, and Reza Salek, eds. Metabolomics. Boca Raton, Florida : CRC Press, [2019]: Chapman and Hall/CRC, 2019. http://dx.doi.org/10.1201/9781315370583.

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Wolfram, Weckwerth. Metabolomics. New Jersey: Humana Press, 2006. http://dx.doi.org/10.1385/1597452440.

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Nielsen, Jens, and Michael C. Jewett, eds. Metabolomics. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-74719-2.

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Bhattacharya, Sanjoy K., ed. Metabolomics. New York, NY: Springer New York, 2019. http://dx.doi.org/10.1007/978-1-4939-9488-5.

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Weckwerth, Wolfram, ed. Metabolomics. Totowa, NJ: Humana Press, 2007. http://dx.doi.org/10.1007/978-1-59745-244-1.

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Wood, Paul L., ed. Metabolomics. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-0864-7.

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Tomita, Masaru, and Takaaki Nishioka, eds. Metabolomics. Tokyo: Springer-Verlag, 2005. http://dx.doi.org/10.1007/4-431-28055-3.

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Soni, Vijay, and Travis E. Hartman, eds. Metabolomics. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-39094-4.

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Hu, Shen, ed. Cancer Metabolomics. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-51652-9.

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Qi, Xiaoquan, Xiaoya Chen, and Yulan Wang, eds. Plant Metabolomics. Dordrecht: Springer Netherlands, 2015. http://dx.doi.org/10.1007/978-94-017-9291-2.

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Book chapters on the topic "Metabolomics"

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Fiehn, Oliver, and Tobias Kind. "Metabolite Profiling in Blood Plasma." In Metabolomics, 3–17. Totowa, NJ: Humana Press, 2007. http://dx.doi.org/10.1007/978-1-59745-244-1_1.

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Kristal, Bruce S., Yevgeniya I. Shurubor, Rima Kaddurah-Daouk, and Wayne R. Matson. "High-Performance Liquid Chromatography Separations Coupled With Coulometric Electrode Array Detectors." In Metabolomics, 159–74. Totowa, NJ: Humana Press, 2007. http://dx.doi.org/10.1007/978-1-59745-244-1_10.

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Nanchen, Annik, Tobias Fuhrer, and Uwe Sauer. "Determination of Metabolic Flux Ratios From 13C-Experiments and Gas Chromatography-Mass Spectrometry Data." In Metabolomics, 177–97. Totowa, NJ: Humana Press, 2007. http://dx.doi.org/10.1007/978-1-59745-244-1_11.

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Schuster, Stefan, Axel Kamp, and Mikhail Pachkov. "Understanding the Roadmap of Metabolism by Pathway Analysis." In Metabolomics, 199–226. Totowa, NJ: Humana Press, 2007. http://dx.doi.org/10.1007/978-1-59745-244-1_12.

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Viant, Mark R. "Revealing the Metabolome of Animal Tissues Using 1H Nuclear Magnetic Resonance Spectroscopy." In Metabolomics, 229–46. Totowa, NJ: Humana Press, 2007. http://dx.doi.org/10.1007/978-1-59745-244-1_13.

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Ott, Karl-Heinz, and Nelly Aranibar. "Nuclear Magnetic Resonance Metabonomics." In Metabolomics, 247–71. Totowa, NJ: Humana Press, 2007. http://dx.doi.org/10.1007/978-1-59745-244-1_14.

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Kikuchi, Jun, and Takashi Hirayama. "Practical Aspects of Uniform Stable Isotope Labeling of Higher Plants for Heteronuclear NMR-Based Metabolomics." In Metabolomics, 273–86. Totowa, NJ: Humana Press, 2007. http://dx.doi.org/10.1007/978-1-59745-244-1_15.

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Erban, Alexander, Nicolas Schauer, Alisdair R. Fernie, and Joachim Kopka. "Nonsupervised Construction and Application of Mass Spectral and Retention Time Index Libraries From Time-of-Flight Gas Chromatography-Mass Spectrometry Metabolite Profiles." In Metabolomics, 19–38. Totowa, NJ: Humana Press, 2007. http://dx.doi.org/10.1007/978-1-59745-244-1_2.

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Tikunov, Yury M., Francel W. A. Verstappen, and Robert D. Hall. "Metabolomic Profiling of Natural Volatiles." In Metabolomics, 39–53. Totowa, NJ: Humana Press, 2007. http://dx.doi.org/10.1007/978-1-59745-244-1_3.

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Morgenthal, Katja, Stefanie Wienkoop, Florian Wolschin, and Wolfram Weckwerth. "Integrative Profiling of Metabolites and Proteins." In Metabolomics, 57–75. Totowa, NJ: Humana Press, 2007. http://dx.doi.org/10.1007/978-1-59745-244-1_4.

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Conference papers on the topic "Metabolomics"

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Farha, S. Y., S. A. A. Comhair, S. Kalhan, R. Zhang, B. Willard, M. Park, J. K. Sharp, K. B. Highland, W. H. W. Tang, and S. C. Erzurum. "Metabolomics in Pulmonary Hypertension." In American Thoracic Society 2019 International Conference, May 17-22, 2019 - Dallas, TX. American Thoracic Society, 2019. http://dx.doi.org/10.1164/ajrccm-conference.2019.199.1_meetingabstracts.a5872.

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Liao, S. Y., C. Restrepo, K. MacPhail, B. Q. Barkes, P. Mroz, C. Riley, T. E. Fingerlin, and L. A. Maier. "Serum Metabolomics in Sarcoidosis." In American Thoracic Society 2022 International Conference, May 13-18, 2022 - San Francisco, CA. American Thoracic Society, 2022. http://dx.doi.org/10.1164/ajrccm-conference.2022.205.1_meetingabstracts.a2142.

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Cakmak, Ali, Xinjian Qi, A. Ercument Cicek, and Gultekin Özsoyoǧlu. "Computational interpretation of metabolomics measurements." In the 2nd ACM Conference. New York, New York, USA: ACM Press, 2011. http://dx.doi.org/10.1145/2147805.2147856.

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MARKLEY, JOHN L., MARK E. ANDERSON, QIU CUI, HAMID R. EGHBALNIA, IAN A. LEWIS, ADRIAN D. HEGEMAN, JING LI, et al. "NEW BIOINFORMATICS RESOURCES FOR METABOLOMICS." In Proceedings of the Pacific Symposium. WORLD SCIENTIFIC, 2006. http://dx.doi.org/10.1142/9789812772435_0016.

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YANG, CHEN, ADAM D. RICHARDSON, JEFFREY W. SMITH, and ANDREI OSTERMAN. "COMPARATIVE METABOLOMICS OF BREAST CANCER." In Proceedings of the Pacific Symposium. WORLD SCIENTIFIC, 2006. http://dx.doi.org/10.1142/9789812772435_0018.

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Goedecke, N., R. Toelke, F. Heer, and A. Hierlemann. "Microsystem for Single-Cell Metabolomics." In TRANSDUCERS 2007 - 2007 International Solid-State Sensors, Actuators and Microsystems Conference. IEEE, 2007. http://dx.doi.org/10.1109/sensor.2007.4300233.

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Verpoorte, R. "From Egon Stahl to Metabolomics." In GA 2017 – Book of Abstracts. Georg Thieme Verlag KG, 2017. http://dx.doi.org/10.1055/s-0037-1608026.

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Chang, Chun, Ying Liang, Juan Wang, Yongchang Sun, and Wanzhen Yao. "Metabolomic profiling differences among asthma, COPD and healthy controls: a LC-MS-based metabolomics analysis." In ERS International Congress 2019 abstracts. European Respiratory Society, 2019. http://dx.doi.org/10.1183/13993003.congress-2019.pa1701.

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Salek, Reza, and Christoph Steinbeck. "Towards standard, accessible and reproducible Metabolomics." In The 1st International Electronic Conference on Metabolomics. Basel, Switzerland: MDPI, 2016. http://dx.doi.org/10.3390/iecm-1-c003.

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González-Domínguez, Raúl, Ana Sayago, and Ángeles Fernández-Recamales. "Comparison of complementary statistical analysis approaches in metabolomic food traceability." In 3rd International Electronic Conference on Metabolomics. Basel, Switzerland: MDPI, 2018. http://dx.doi.org/10.3390/iecm-3-05839.

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Reports on the topic "Metabolomics"

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Rabinowitz, Joshua D., Ludmilla Aristilde, and Daniel Amador-Noguez. Metabolomics of Clostridial Biofuel Production. Office of Scientific and Technical Information (OSTI), September 2015. http://dx.doi.org/10.2172/1213974.

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Vertes, Akos. New approaches for metabolomics by mass spectrometry. Office of Scientific and Technical Information (OSTI), July 2017. http://dx.doi.org/10.2172/1368638.

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Poole, Elizabeth M. Psychosocial Stress and Ovarian Cancer Risk: Metabolomics and Perceived Stress. Fort Belvoir, VA: Defense Technical Information Center, October 2014. http://dx.doi.org/10.21236/ada613203.

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Joslyn, Cliff, Sean Colby, Aivett Bilbao, Corey Broeckling, Andy Lin, Emilie AH Purvine, and Madelyn Shapiro. Molecular Hypernetworks for Exploration of Multi-Dimensional Metabolomics Data (Chyper). Office of Scientific and Technical Information (OSTI), September 2023. http://dx.doi.org/10.2172/2242495.

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Tran, Ly Cong, My Hoang Le, Hung Viet Phan, Thi Nguyen Thao Nguyen, Nhu Thi Huynh Tran, Quan Minh Pham, Duc Long Tran, Thu Vo-Pham-Minh, and Phuong Minh Nguyen. Current Perspective of Metabolomics in Pediatric Nephrotic Syndrome: A Systematic Review. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, January 2024. http://dx.doi.org/10.37766/inplasy2024.1.0058.

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PI: Lily Y. Young Co-PI: Gerben J. Zylstra. Conference-EC-US Task Force Joint US-EU Workshop on Metabolomics and Environmental Biotechnology. Office of Scientific and Technical Information (OSTI), June 2009. http://dx.doi.org/10.2172/1039555.

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Rabinowitz, Joshua D. Final Technical Report--Quantitative analysis of metabolic regulation by integration of metabolomics, proteomics, and fluxomics. Office of Scientific and Technical Information (OSTI), December 2018. http://dx.doi.org/10.2172/1487155.

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Clendinen, Chaevien, Javier Flores, Lisa Bramer, David Degnan, Vanessa Paurus, and Yuri Eberlim de Corilo. Enter Gaussian Mixture Modeling Extensions for Improved False Discovery Rate Estimation in GC-MS Metabolomics. Office of Scientific and Technical Information (OSTI), January 2023. http://dx.doi.org/10.2172/1985304.

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Siuzdak, Gary. Ecosystems and Networks Integrated with Genes and Molecular Assemblies (ENIGMA): Integrating Metabolomics into Environmental Systems Biology. Office of Scientific and Technical Information (OSTI), March 2023. http://dx.doi.org/10.2172/1963932.

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Lidstrom, Mary E., Ludmila Chistoserdova, Marina G. Kalyuzhnaya, Victoria J. Orphan, and David A. Beck. Systems level insights into alternate methane cycling modes in a freshwater lake via community transcriptomics, metabolomics and nano-SIMS analysis. Office of Scientific and Technical Information (OSTI), August 2014. http://dx.doi.org/10.2172/1149958.

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