NEXT GENERATION SEQUENCING TECHNOLOGIES
What you will learn
understand the importance of data abnalysis
how big data needs a computational approach
diffrent mathematical theoris for analysis of genomic data
applications of mathematics in biological data analysis
Why take this course?
Course Title: Data Science for Biology
Course Description: Data Science for Biology introduces students to the principles and techniques of data science, focusing on their application to biological data. This course covers essential topics such as genomic data analysis, bioinformatics, and systems biology. Students will learn how to process and analyze large-scale biological datasets using computational tools and statistical methods. Key concepts include DNA sequencing, RNA-seq data analysis, genome-wide association studies (GWAS), and protein structure prediction.
The course provides hands-on experience with popular bioinformatics software and programming languages such as R and Python. Students will engage in projects that involve real-world biological data, developing skills in data visualization, machine learning, and network analysis. By the end of the course, students will be equipped to handle complex biological datasets, perform integrative analyses, and derive meaningful insights that can drive scientific discovery and innovation.
This course is suitable for biology students seeking to enhance their computational skills, as well as data science students interested in applying their expertise to biological problems. Prerequisites include basic knowledge of biology and programming. Through lectures, practical sessions, and project work, students will gain a comprehensive understanding of how data science tools can transform biological research. LETS START