Advanced Certificate in Structural Bioinformatics: Drug Discovery
-- ViewingNowThe Advanced Certificate in Structural Bioinformatics: Drug Discovery is a comprehensive course designed to equip learners with essential skills in the field of bioinformatics and drug discovery. This course emphasizes the importance of understanding the 3D structures of biological macromolecules and their interactions, which is crucial for the development of novel therapeutic strategies.
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ร 2-3 heures par semaine
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Dรฉtails du cours
โข Advanced Bioinformatics Algorithms: This unit will cover the advanced algorithms and data structures that are commonly used in structural bioinformatics and drug discovery, including graph algorithms, machine learning, and data mining techniques.
โข Protein Structure Prediction: This unit will focus on the methods and tools used to predict protein structure, including homology modeling, ab initio methods, and molecular dynamics simulations.
โข Molecular Docking and Virtual Screening: This unit will cover the principles and applications of molecular docking and virtual screening in drug discovery, including ligand-protein interactions, scoring functions, and lead optimization.
โข Pharmacophore Modeling and 3D Quantitative Structure-Activity Relationship (3D-QSAR): This unit will explore the concepts and techniques used in pharmacophore modeling and 3D-QSAR, including feature-based methods, comparative molecular field analysis, and machine learning algorithms.
โข Systems Biology and Network Analysis: This unit will introduce the principles of systems biology and network analysis in drug discovery, including protein-protein interaction networks, gene regulatory networks, and pathway analysis.
โข Biological Data Management and Analysis: This unit will cover the best practices and tools for managing and analyzing large-scale biological data, including databases, data visualization, and statistical methods.
โข Computational Toxicology: This unit will explore the application of computational methods in toxicology, including predictive toxicology, read-across, and in silico methods for hazard assessment.
โข Regulatory and Ethical Considerations in Drug Discovery: This unit will discuss the ethical and regulatory considerations in drug discovery, including data privacy, intellectual property, and regulatory compliance.
Parcours professionnel
Exigences d'admission
- Comprรฉhension de base de la matiรจre
- Maรฎtrise de la langue anglaise
- Accรจs ร l'ordinateur et ร Internet
- Compรฉtences informatiques de base
- Dรฉvouement pour terminer le cours
Aucune qualification formelle prรฉalable requise. Cours conรงu pour l'accessibilitรฉ.
Statut du cours
Ce cours fournit des connaissances et des compรฉtences pratiques pour le dรฉveloppement professionnel. Il est :
- Non accrรฉditรฉ par un organisme reconnu
- Non rรฉglementรฉ par une institution autorisรฉe
- Complรฉmentaire aux qualifications formelles
Vous recevrez un certificat de rรฉussite en terminant avec succรจs le cours.
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Frais de cours
- 3-4 heures par semaine
- Livraison anticipรฉe du certificat
- Inscription ouverte - commencez quand vous voulez
- 2-3 heures par semaine
- Livraison rรฉguliรจre du certificat
- Inscription ouverte - commencez quand vous voulez
- Accรจs complet au cours
- Certificat numรฉrique
- Supports de cours
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