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Metabolomics and Network Pharmacology Research Technology and Practice Training Course Notice

 Last Update: 2022-08-30
 Source: Internet
 Author: User

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Time: September 17-18, 2022
Online live courses, free replay videos, long-term Q&A

【Course Background】【Course Features】【Teacher】【Course Introduction】

time	Lecture topic	Course Contents
9:00-12:00 am on the first day	Metabolomics Research Technology and Practice	1. Metabolomics research ideas and processes, and a global understanding of new directions in the field of metabolism 1. 1 Overview of metabolomics1. 2 Notes on collection, preservation, and preparation ofmetabolomics samples2. 1 Introduction to metabolomics-related platforms2. 2 Introduction to commonly used software and databases (data acquisition, data preprocessing, metabolite identification)2. 3 Data preprocessing and analysis 3. Metabolomics based on SIMCA-P software Multivariate statistical analysis and practice of academic data3. 1 Sample classification (PCA, PLS-DA, OPLS-DA)3. 2 Differential variable screening (S-plot, S+V-plot, VIP, etc. )3. 3 Interpretation of common graphic results
14:00-17:00 pm on the first day	Network Pharmacology Research Technology and Practice	4. Network pharmacology research ideas and processes 5. Network pharmacology data analysis and practice 5. 1 Acquisition and screening of chemical components (Pubchem, TCMSP database, TCMID database, Swiss ADME database, etc. ) 5. 2 Acquisition of chemical components of traditional Chinese medicine (TCMSP database ) , BATMAN-TCM database, Similarity Ensemble Approach (SEA) database, Swiss Target Prediction database, HIT2. 0, HERB, etc. ) 5. 3 Disease target enrichment database (DisGeNET database, GeneCards database, OMIM database, etc. ) 5. 4 Compounds and disease targets Mapping (Venn diagram) 5. 5 PPI network analysis (PPI network construction, screening of core nodes) 5. 6 Enrichment analysis (DAVID database, Metascape database, KOBAS database) 5. 7 Pathway visualization analysis tools (bubble chart, histogram) 5. 8 Target organization Positioning Analysis 5. 9 Network Diagram Construction—Cytoscape (Data Import, Node Relationship Establishment, Node Attribute Calculation, Adjustment of Network Style, Screening and Filtering, Network Diagram Export)
9:00-12:00 am the next day	Technology and Practice of Combination of Metabolomics and Network Pharmacology	6. Research ideas for the combination of metabolomics and network pharmacology 7. Combined analysis technology of metabolomics and network pharmacology 7. 1 Acquisition of metabolomics and network pharmacology data (HMDB database, component target acquisition, disease target enrichment database 7. 2 Metabolomics function analysis (enrichment analysis, pathway analysis, etc. ) 7. 3 Metabolomics small molecule network association analysis (Metscape software, OmicsNet database) 7. 4 Metabolomics and network pharmacology function hierarchy analysis
14:00-17:00 pm the next day	Literature Interpretation and Case Analysis	8. Literature Interpretation: Article Analysis Process and Routine Combining Metabolomics and Network Pharmacology 8. 1 Example of Network Analysis of Targets of Chemical Components of Traditional Chinese Medicine and Metabolic Small Molecules (Food Res Int. 2020, 136:109503) Innovation: Using Metscape software to analyze The differential metabolites discovered by metabolomics are related to the drug targets of traditional Chinese medicine components, focusing on key proteins . 8. 2 Example of functional hierarchical association analysis between metabolomics and network pharmacology (JEthnopharmacol. 2021, 264:113281. ) Innovation point: Use functional enrichment tools to correlate network pharmacology and metabolomics data respectively, focusing on key pathways . 8. 3 Example of Metabolomics and Network Pharmacology Association Analysis (Comput Struct Biotechnol J. 2021, 19:1002-1013) Innovation point: Integrating metabolomics and network pharmacology, starting from metabolic small molecule network and metabolomics functional analysis, many Dimensions focus on key pathways and key proteins . 9. Example analysis and practice 9. 1 TCMSP database acquisition and screening of chemical components 9. 2 Swiss Target Prediction database to predict component targets 9. 3 DisGeNET database to obtain disease targets 9. 4 Compound and disease target mapping 9. 5 PPI network drawing 9. 6 DAVID software for enrichment analysis 9. 7 Cytoscape Tool to draw component-target map 9. 8 Metscape draws a metabolism-enzyme network correlation map

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