BPS3031
Computational drug design
基本信息
| 学分 | 6 credit points |
|---|---|
| 开课学期 | First semester |
| 校区 | Malaysia |
| 考核构成 | Workshop tasks — 30% Final assessment — 50% Mid-semester test — 20% |
开课安排1 条
| 教学期 | 授课方式 | 状态 |
|---|---|---|
| First semester | Teaching activities are on-campus (ON-CAMPUS) | 开课 |
以上为该校区在官方资料中登记的全部开课安排，不是汇总。同一门课可能在多个 教学期开课，也可能不同教学期的授课方式不同。
课程简介
This unit introduces you to the key concepts and practical application of computational methods in chemistry and drug discovery. The unit will teach fundamental programming skills using the widely-used programming language Python and apply them to the key skills of as data visualization, chemoinformatics, and machine learning. It will cover important molecular modelling methods including molecular docking, molecular dynamics, and quantum mechanical calculations, as well as bioinformatics methods. You will learn to use molecular modelling software and to construct and validate QSAR models, use supervised and unsupervised learning techniques, and to critically evaluate the role of computational tools in drug development.
以上为 Monash Handbook 的官方原文，版权属 Monash University，此处按本站要求转载并标注出处： 官方页面 ↗
学习成果6 条
官方原文（Learning outcomes），版权属 Monash University。
- ULO1 Apply fundamental programming skills using the programming language Python, including using use of variables, conditionals, loops, functions and data visualization
- ULO2 Utilise molecular modelling techniques including molecular docking, molecular dynamics, and basic quantum mechanical calculations using computational chemistry software
- ULO3 Use QSAR and chemoinformatics techniques to analyse molecular and biological data.
- ULO4 Build, validate, and interpret statistical and machine learning models for regression and classification in chemistry
- ULO5 Perform bioinformatics tasks such as sequence alignment and BLAST searches
- ULO6 Critically analyse the use of computational methods in drug development
教学方式与预期工作量
教学方式
Enquiry-based learning
Problem-based learning
Active learning
Online learning
预期工作量
• Twelve 1-hour online modules (discovery)
• Twenty-four 1-hour interactive lectures (online modules)
• Six 2-hour Q&A sessions
• Ten 3-hour workshops
• One hour of scheduled assessment
官方原文，版权属 Monash University。
先修 / 同修要求
以下先修关系按官方来源的结构化先修字段解析，原始记号：BPS2022
先修链路
按官方先修字段的原始分组展开，AND / OR 的区别保留着—— 「A 或 B」和「A 与 B」在选课时是两回事。每门课点进去可以继续往下看。
属于这些学位1 个
这门课出现在下列学位的官方结构里。反过来说：如果你读的是这些学位之一，它大概率是要修的 （必修还是选修取决于它在 Part 里的位置，点进去看结构）。
数据来源
- 数据来源
- 官方网页
handbook.monash.edu ↗ - 抓取时间
- 2026-09-13
- 可信度
- 程序抓取，未人工核实
查看官方完整描述 ↗ — 事实性字段（代码、学分、教学期、授课方式、考核权重、先修/同修/互斥关系）与 课程简介、学习成果、教学方式、预期工作量均取自官方 Handbook； 正文版权属 Monash University，此处转载并逐处标注出处。
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