WebSpecmine: A Website for Metabolomics Data Analysis and Mining

Cardoso, Sara; Afonso, Telma; Maraschin, Marcelo; Rocha, Miguel

doi:10.3390/metabo9100237

Cited by 12 publications

(9 citation statements)

References 11 publications

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“…At present, there are several tools available for processing metabolomic data. Some of these tools cover the entire metabolomics workflows, including the data processing step, such as IP4M (Liang et al , 2020 ), KIMBLE (Verhoeven et al , 2018 ), MetaboAnalyst (Xia & Wishart, 2011 ), MetaDB (Franceschi et al , 2014 ), Metandem (Hao et al , 2019 ), MetFlow (Shen & Zhu, 2019 ), Workflow4Metabolomics (Giacomoni et al , 2015 ), WebSpecmine (Cardoso et al , 2019 ), and XCMS (Forsberg et al , 2018 ). These tools have also been used in immunology research.…”

Section: Data Preprocessing and Processing Methods Applied On Metabol...mentioning

confidence: 99%

Metabolomics meets systems immunology

Zhu

et al. 2023

EMBO Reports

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Metabolic processes play a critical role in immune regulation. Metabolomics is the systematic analysis of small molecules (metabolites) in organisms or biological samples, providing an opportunity to comprehensively study interactions between metabolism and immunity in physiology and disease. Integrating metabolomics into systems immunology allows the exploration of the interactions of multilayered features in the biological system and the molecular regulatory mechanism of these features. Here, we provide an overview on recent technological developments of metabolomic applications in immunological research. To begin, two widely used metabolomics approaches are compared: targeted and untargeted metabolomics. Then, we provide a comprehensive overview of the analysis workflow and the computational tools available, including sample preparation, raw spectra data preprocessing, data processing, statistical analysis, and interpretation. Third, we describe how to integrate metabolomics with other omics approaches in immunological studies using available tools. Finally, we discuss new developments in metabolomics and its prospects for immunology research. This review provides guidance to researchers using metabolomics and multiomics in immunity research, thus facilitating the application of systems immunology to disease research.

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Section: Data Preprocessing and Processing Methods Applied On Metabol...mentioning

confidence: 99%

Metabolomics meets systems immunology

Zhu

et al. 2023

EMBO Reports

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“…Thus, the state-of-the-art understanding of cell metabolism can be improved and further combined with mechanistic models to automate synthetic biology and intelligent biomanufacturing (Oyetunde et al, 2018 ). To this end, recent advancements in metabolomics tools for data analysis, storing and sharing have been developed [e.g., WebSpecmine (Cardoso et al, 2019 ), SIRIUS 4 (Dührkop et al, 2019 ), MetaboAnalyst 4.0 (Chong et al, 2018 ), and SECIM (Kirpich et al, 2018 )]. Knowledge of biology (e.g., regulation, metabolism, physiology, etc.)…”

Section: A Comparison Of the Major “Omics” Technologiesmentioning

confidence: 99%

Omics-Driven Biotechnology for Industrial Applications

Amer

Baidoo

2021

Front. Bioeng. Biotechnol.

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Biomanufacturing is a key component of biotechnology that uses biological systems to produce bioproducts of commercial relevance, which are of great interest to the energy, material, pharmaceutical, food, and agriculture industries. Biotechnology-based approaches, such as synthetic biology and metabolic engineering are heavily reliant on “omics” driven systems biology to characterize and understand metabolic networks. Knowledge gained from systems biology experiments aid the development of synthetic biology tools and the advancement of metabolic engineering studies toward establishing robust industrial biomanufacturing platforms. In this review, we discuss recent advances in “omics” technologies, compare the pros and cons of the different “omics” technologies, and discuss the necessary requirements for carrying out multi-omics experiments. We highlight the influence of “omics” technologies on the production of biofuels and bioproducts by metabolic engineering. Finally, we discuss the application of “omics” technologies to agricultural and food biotechnology, and review the impact of “omics” on current COVID-19 research.

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“…To date, the multivariate statistical tools developed, mainly through SIMCA-P software (Umetrics, Sweden), comprise three major techniques: unsupervised, supervised, and pathway analysis [101]. Principal component analysis (PCA), the most commonly used unsupervised tool, converts a large number of related datasets into a limited number of variables to visualize the most important trends after dimensionality reduction [102]. Partial least squares discriminant analysis (PLS-DA) and orthogonal partial least squares discriminant analysis (OPLS-DA) are usually used to assess obvious differences between the groups (variables) within datasets and identify the biomarkers through the value of variables of importance in projection (VIP) [102,103].…”

Section: Metabolomic Analyses Based On Data Interpretation and Multivariate Statisticsmentioning

confidence: 99%

“…Principal component analysis (PCA), the most commonly used unsupervised tool, converts a large number of related datasets into a limited number of variables to visualize the most important trends after dimensionality reduction [102]. Partial least squares discriminant analysis (PLS-DA) and orthogonal partial least squares discriminant analysis (OPLS-DA) are usually used to assess obvious differences between the groups (variables) within datasets and identify the biomarkers through the value of variables of importance in projection (VIP) [102,103]. Regarding pathway analysis, pathway enrichment analysis of differential metabolites is mainly based on the Kyoto Encyclopedia of Genes and Genomes (KEGG, https://www.genome.jp/kegg/, accessed on 30 June 2021) database or MetaboAnalyst (https://www.metaboanalyst.ca/, accessed on 30 June 2021), which helps understand the mechanisms of metabolic pathway changes in a sample [99].…”

Section: Metabolomic Analyses Based On Data Interpretation and Multivariate Statisticsmentioning

confidence: 99%

Metabolomics Approaches for the Comprehensive Evaluation of Fermented Foods: A Review

Gao

Hou

Gao

et al. 2021

Foods

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Fermentation is an important process that can provide new flavors and nutritional and functional foods, to deal with changing consumer preferences. Fermented foods have complex chemical components that can modulate unique qualitative properties. Consequently, monitoring the small molecular metabolites in fermented food is critical to clarify its qualitative properties and help deliver personalized nutrition. In recent years, the application of metabolomics to nutrition research of fermented foods has expanded. In this review, we examine the application of metabolomics technologies in food, with a primary focus on the different analytical approaches suitable for food metabolomics and discuss the advantages and disadvantages of these approaches. In addition, we summarize emerging studies applying metabolomics in the comprehensive analysis of the flavor, nutrition, function, and safety of fermented foods, as well as emphasize the applicability of metabolomics in characterizing the qualitative properties of fermented foods.

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WebSpecmine: A Website for Metabolomics Data Analysis and Mining

Cited by 12 publications

References 11 publications

Metabolomics meets systems immunology

Metabolomics meets systems immunology

Omics-Driven Biotechnology for Industrial Applications

Metabolomics Approaches for the Comprehensive Evaluation of Fermented Foods: A Review

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