Masterclass Certificate in Metabolomic Workflows
-- ViewingNowThe Masterclass Certificate in Metabolomic Workflows is a comprehensive course that provides in-depth knowledge and training in metabolomics, a rapidly growing field. This course is essential for learners seeking to understand and apply metabolomic workflows in various industries, including healthcare, biotechnology, pharmaceuticals, and agriculture.
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โข Metabolomics Fundamentals: Introduction to metabolomics, metabolome definition, primary and secondary metabolites, metabolic pathways, and the importance of metabolomics in systems biology.
โข Sample Preparation and Extraction: Overview of various sample preparation techniques, extraction methods, and quality control for metabolomics experiments.
โข Analytical Techniques in Metabolomics: Detailed exploration of popular analytical techniques such as liquid/gas chromatography (LC/GC), mass spectrometry (MS), and nuclear magnetic resonance (NMR) spectroscopy.
โข Data Processing and Annotation: Hands-on training for data processing, metabolite identification, and annotation using open-source and commercial software.
โข Data Analysis and Statistical Methods: Comprehensive review of multivariate data analysis techniques, univariate statistical tests, and machine learning algorithms for metabolomics data interpretation.
โข Integration of Metabolomics with Other Omics Data: Best practices for integrating metabolomics with other omics data such as genomics, transcriptomics, and proteomics to gain a holistic understanding of biological systems.
โข Advanced Metabolomics Workflows: Deep dive into cutting-edge workflows for targeted and untargeted metabolomics, metabolic flux analysis, and spatial metabolomics.
โข Metabolomics Applications in Health and Disease: Exploration of metabolomics applications in various fields, including biomarker discovery, precision medicine, drug development, and plant/animal research.
โข Data Management, Sharing, and Ethical Considerations: Guidelines for managing, sharing, and storing metabolomics data following FAIR principles and best ethical practices.
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