AI and Bioinformatics: Genomic Data Analysis

Gain practical skills in using WEKA

This three-week course from Taipei Medical University follows on from the online short course ‘Artificial Intelligence in Bioinformatics’ to help you master AI techniques in the field of bioinformatics.

Through real-world case studies, such as the design and discovery of drugs, you’ll learn how AI and machine learning are transforming bioinformatics.

You’ll also gain practical skills as you learn how to use WEKA, a Java software with a collection of machine learning algorithms, to collect and analyse bioinformatics data.

Discover AI applications in bioinformatics research, such as genome sequencing

You’ll develop your understanding of AI-based bioinformatics research, including genome sequencing, protein function prediction, and gene expression examination.

With this knowledge, you’ll be able to interpret biological data and provide statistical information.

Understand a Convolutional Neural Network and other deep learning concepts

Next, you’ll explore the foundations of deep learning to understand how AI can process data in a way similar to the human brain.

You’ll delve into core concepts such as Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), and Natural Language Processing before unpacking their applications in bioinformatics.

Build your AI toolkit for working in bioinformatics

Finally, you’ll develop the knowledge and skills you need to apply AI in practice.

Mastering WEKA, you’ll learn how to use the tool to help with your professional research in bioinformatics. You’ll also gain the skills to write bioinformatics papers as you explore research flowcharts and data visualisation.

By the end of the course, you’ll have the skills to drive innovation in bioinformatics.

This course is designed for any student, biologist, or researcher who would like to learn the basics of using AI to study bioinformatics data.

It follows on from our short course ‘Artificial Intelligence in Bioinformatics’ which we recommend taking first to develop your foundation of knowledge beforehand.

• Feature Learning
• Review of AI in Bioinformatics
• Feature Learning
• Deep Learning
• Deep learning algorithm
• Deep learning and bioinformatics
• Weka and Deep Learning
• Writing Bioinformatics Papers
• Research Flowchart and Dabta Visualization
• Bioinformatics Paper Example
• Assessment Time