In recent years, the FAIR guiding principles and the broader concept of open science has grown in importance in academic research, especially as funding entities have aggressively promoted public sharing of research products. Key to public research s...
The novel coronavirus SARS-CoV-2 has spread across the world since 2019, causing a global pandemic. The pathogenesis of the viral infection and the associated clinical presentations depend primarily on host factors such as age and immunity, rather th...
Mass spectrometry-based metabolomics approaches generate high-dimensional datasets that enable comprehensive profiling of metabolites and other biomolecules. However, these datasets are influenced by multiple sources of variability, including both th...
Background/Objectives: Metabolism-level interpretation of metabolomics datasets requires aggregation analyses across metabolites. One highly used aggregation analysis is pathway enrichment analysis (PEA), which involves detecting pathways enriched wi...
High exercise loading causes intricate and ambiguous proteomic and metabolic changes. This study aims to describe the dataset on protein and metabolite contents in plasma samples collected from highly trained athletes across different sports discipli...
Citrus fruits are valued not only for their nutritional benefits but also for their rich phytochemical content. Metabolomics has emerged as a comprehensive technique for assessing the chemical composition of fruits. The botanical connection between l...
Even with the widespread use of liquid chromatography mass spectrometry (LC/MS) based metabolomics, there are still a number of challenges facing this promising technique. Many, diverse experimental workflows exist; yet there is a lack of infrastruct...
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...
Congenital lactic acidosis (CLA) is a rare condition in most instances due to a range of inborn errors of metabolism that result in defective mitochondrial function. Even though the implementation of next generation sequencing has been rapid, the dia...
Metabolomics generates massive and complex data. Redundant different analytical species and the high degree of correlation in datasets is a constraint for the use of data mining/statistical methods and interpretation. In this context, we developed a...
Liquid chromatography–high-resolution mass spectrometry (LC-HRMS), as applied to untargeted metabolomics, enables the simultaneous detection of thousands of small molecules, generating complex datasets. Alignment is a crucial step in data proce...
Mouse knockouts facilitate the study ofgene functions. Often, multiple abnormal phenotypes are induced when a gene is inactivated. The International Mouse Phenotyping Consortium (IMPC) has generated thousands of mouse knockouts and catalogued their p...
Data integration has been proven to provide valuable information. The information extracted using data integration in the form of multiblock analysis can pinpoint both common and unique trends in the different blocks. When working with small multiblo...
The study of the relationship between cultivated plants and environmental factors can provide information ranging from a deeper understanding of the plant biological system to the development of more effective management strategies for improving yiel...
This study aims to compare the metabolomic profiles of Malaysian and New Zealand honey while determining their anti-oncogenic activity for potential prophylactic functions. Metabolomics tools including multivariate analysis were applied on concatenat...
Background: Post-exercise recovery involves coordinated metabolic restoration and redox rebalancing. Although dietary polyphenols have been proposed to facilitate recovery, the metabolic mechanisms underlying their effects—particularly during t...
Background/Objectives: Metabolomics has recently emerged as a key tool in the biological sciences, offering insights into metabolic pathways and processes. Over the last decade, network-based machine learning approaches have gained significant popula...
Metabolomics methods often encounter trade-offs between quantification accuracy and coverage, with truly comprehensive coverage only attainable through a multitude of complementary assays. Due to the lack of standardization and the variety of metabol...
Untargeted metabolomics (UM) is increasingly being deployed as a strategy for screening patients that are suspected of having an inborn error of metabolism (IEM). In this study, we examined the potential of existing outlier detection methods to detec...
Glioblastoma (GBM) is a fatal brain cancer known for its rapid and aggressive growth, with some studies indicating that females may have better survival outcomes compared to males. While sex differences in GBM have been observed, the underlying biolo...
Tracer metabolomics is a powerful technology for the biomedical community to study and understand disease-inflicted metabolic mechanisms. However, the interpretation of tracer metabolomics results is highly technical, as the metabolites’ abunda...
Global metabolomics based on high-resolution liquid chromatography mass spectrometry (LC-MS) has been increasingly employed in recent large-scale multi-omics studies. Processing and interpretation of these complex metabolomics datasets have become a...
Untargeted metabolomic studies generate information-rich, high-dimensional, and complex datasets that remain challenging to handle and fully exploit. Despite the remarkable progress in the development of tools and algorithms, the “exhaustive” extract...
Data analysis for metabolomics is undergoing rapid progress thanks to the proliferation of novel tools and the standardization of existing workflows. As untargeted metabolomics datasets and experiments continue to increase in size and complexity, sta...
The goals of metabolic engineering are well-served by the biological information provided by metabolomics: information on how the cell is currently using its biochemical resources is perhaps one of the best ways to inform strategies to engineer a cel...
Stable isotope resolved metabolomics (SIRM) experiments use stable isotope tracers to provide superior metabolomics datasets for metabolic flux analysis and metabolic modeling. Since assumptions of model correctness can seriously compromise interpret...
Untargeted metabolomics based on liquid chromatography coupled with mass spectrometry (LC–MS) can detect thousands of features in samples and produce highly complex datasets. The accurate extraction of meaningful features and the building of discrimi...
Emerging technologies now allow for mass spectrometry-based profiling of thousands of small molecule metabolites (‘metabolomics’) in an increasing number of biosamples. While offering great promise for insight into the pathogenesis of hum...
As the ability to collect profiling data in metabolomics increases substantially with the advances in Liquid Chromatography–Mass Spectrometry (LC-MS) instruments, it is urgent to develop new and powerful data analysis approaches to match the bi...
Temporal associations in longitudinal nontargeted metabolomics data are generally ignored by common pattern recognition methods such as partial least squares discriminant analysis (PLS-DA) and orthogonal partial least squares discriminant analysis (O...
Metabolomics is the systematic study of the small-molecule profiles of biological samples produced by specific cellular processes. The high-throughput technologies used in metabolomic investigations generate datasets where variables are strongly corr...
The Omics Dashboard is a software tool for interactive exploration and analysis of metabolomics, transcriptomics, proteomics, and multi-omics datasets. Organized as a hierarchy of cellular systems, the Dashboard at its highest level contains graphica...
Dietary factors modulate interactions between the microbiome, metabolome, and immune system. Sulforaphane (SFN) exerts effects on aging, cancer prevention and reducing insulin resistance. This study investigated effects of SFN on the gut microbiome a...
Glioblastoma (GBM) is a highly malignant and devastating brain cancer characterized by its ability to rapidly and aggressively grow, infiltrating brain tissue, with nearly universal recurrence after the standard of care (SOC), which comprises maximal...
Metabolomics encounters challenges in cross-study comparisons due to diverse metabolite nomenclature and reporting practices. To bridge this gap, we introduce the Metabolites Merging Strategy (MMS), offering a systematic framework to harmonize multip...
Motivation: Untargeted metabolomics comprehensively characterizes small molecules and elucidates activities of biochemical pathways within a biological sample. Despite computational advances, interpreting collected measurements and determining their...
Nuclear magnetic resonance (NMR) spectroscopy is well-established to address questions in large-scale untargeted metabolomics. Although several approaches in data processing and analysis are available, significant issues remain. NMR spectroscopy of u...
The breeding of stress-tolerant cultivated plants that would allow for a reduction in harvest losses and undesirable decrease in quality attributes requires a new quality of knowledge on molecular markers associated with relevant agronomic traits, on...
Wine origin and ageing are two factors related to wine quality which in turn is associated to wine metabolome. Currently, new metabolomic techniques and proper statistics procedures allow accurate profiling of wine metabolome. Thus, the main goal was...
Metabolomics uses quantitative analyses of metabolites from tissues or bodily fluids to acquire a functional readout of the physiological state. Complex diseases arise from the influence of multiple factors, such as genetics, environment and lifestyl...
Over the past decades, pathway analysis has become one of the most commonly used approaches for the functional interpretation of metabolomics data. Although the approach is widely used, it is not well standardized and the impact of different methodol...
Several metabolomic software programs provide methods for peak picking, retention time alignment and quantification of metabolite features in LC/MS-based metabolomics. Statistical analysis, however, is needed in order to discover those features signi...
Previous work demonstrated that serum metabolomics can distinguish pancreatic cancer from benign disease. However, in the clinic, non-pancreatic periampullary cancers are difficult to distinguish from pancreatic cancer. Therefore, to test the clinica...
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 metabol...
Absolute quantification of intracellular metabolite pools is a prerequisite for modeling and in-depth biological interpretation of metabolomics data. It is the final step of an elaborate metabolomics workflow, with challenges associated with all step...
Statistical classification is a critical component of utilizing metabolomics data for examining the molecular determinants of phenotypes. Despite this, a comprehensive and rigorous evaluation of the accuracy of classification techniques for phenotype...
The effects of low doses of toxicants are often subtle and information extracted from metabolomic data alone may not always be sufficient. As end products of enzymatic reactions, metabolites represent the final phenotypic expression of an organism an...
Introduction: Transcranial direct current stimulation (tDCS) is an evolving non-invasive neurostimulation technique. Despite multiple studies, its underlying molecular mechanisms are still unclear. Several previous human studies of the effect of tDCS...
To represent the composition of small molecules circulating in HepG2 cells and the formation of the “core” of characteristic metabolites that often attract researchers’ attention, we conducted a meta-analysis of 56 datasets obtained...
Appropriate experimental design and sample preparation are key steps in metabolomics experiments, highly influencing the biological interpretation of the results. The sample preparation workflow for plant metabolomics studies includes several steps b...
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