Basic Introduction to Network Pharmacology
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৳900.00
/ ৳1000.00 -
10 Lectures
This course provides a comprehensive entry into Network Pharmacology, a holistic approach that revolutionizes modern drug discovery by analyzing the complex interactions between drugs, targets, and diseases. It guides learners through the complete research pipeline: from mining bioactive compounds and gene targets to constructing complex networks using Cytoscape. Students will master topological analysis to identify core targets and perform GO & KEGG enrichment to decipher biological mechanisms. The curriculum ensures students can scientifically validate and visualize multi-target drug mechanisms effectively.
Description
Course Overview: Welcome to the era of Systems Biology. This course is meticulously designed to introduce beginners to Network Pharmacology, a field that shifts the focus from the traditional "one drug, one target" approach to a holistic "multi-component, multi-target" strategy. Whether you are researching herbal medicines, repurposing drugs, or studying complex diseases, this course provides the essential roadmap to understanding how drugs affect biological networks as a whole.
What You Will Learn: We have structured the curriculum into 3 distinct modules covering 10 comprehensive classes, taking you from data collection to the visualization of complex biological mechanisms.
Module 1: Foundations & Data Mining: Understand the core shift from reductionist to holistic pharmacology. Learn how to professionally mine data using major databases (like TCMSP, GeneCards, and OMIM) to identify bioactive compounds and their potential disease targets.
Module 2: Network Construction & Topology: Dive into the technical heart of the field. Learn to use Cytoscape, the industry-standard software for network visualization. Master the construction of Protein-Protein Interaction (PPI) networks and learn how to use mathematical algorithms to identify "Hub Genes"—the most critical targets in your study.
Module 3: Functional Enrichment & Visualization: Move from data to biological meaning. Learn how to perform Gene Ontology (GO) and KEGG Pathway analysis to explain how a drug works in the body. Finally, master the art of creating high-quality network visuals suitable for scientific journals.
Who Should Attend:
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Undergraduate and Postgraduate students in Pharmacy, Bioinformatics, and Biotechnology.
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Researchers in Natural Product Chemistry, Ayurveda, or TCM looking to modernize their research.
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Anyone interested in Systems Biology and Polypharmacology.
Outcome: By the end of this course, you will have a solid theoretical understanding of Network Pharmacology, the practical skills to use Cytoscape and enrichment tools, and the ability to independently conduct and publish network-based drug research.
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