Applied Bio-Informatics (2 Units; Elective; L = 15; P = 45)
Course Outline
Bioinformatics tools and techniques for analyzing biological data. Statistical methods used in bioinformatics and their application in data analysis. Data visualization and machine learning principles in bioinformatics research. Network analysis and its application in understanding biological systems. Importance of bioinformatics in healthcare, agriculture, and biotechnology. Ethical issues associated with bioinformatics research and use of biological data. Hands-on experience with bioinformatics tools and databases. Problem-solving skills development through projects and research. Career opportunities in bioinformatics and related fields. Theoretical and practical aspects of bioinformatics. Current challenges in the field of bioinformatics and ongoing efforts to address them. Latest advancements in bioinformatics research. Foundation for further study in bioinformatics. Experience working with real-world biological data. Data analysis and interpretation techniques used in various biological domains. Application of bioinformatics methods to solve real-world problems. Comprehensive overview of the field of bioinformatics.
- Teacher: LMS Admin