Course Details Language of Instruction English Level of Course Unit Bachelor's Degree Department / Program COMPUTER ENGINEERING Type of Program Formal Education Type of Course Unit Elective Course Delivery Method Face To Face Objectives of the Course Learn different types and sources of big data (-omics data) available in molecular biology, Learn the computational methodologies for the analysis of various biological high throughput datasets, massively parallel sequencing datasets, Learn a set of algorithms that have important applications in computational genomics, but which have key applications in other fields as well. Apply the concepts learned to a real problem and convert the molecular data into medical knowledge. Course Content Following the Human Genome Project, the recent revolution in genomic technologies has enabled the generation of massive amounts of “omics” data. The challenge in this new era is to develop computational methods for integrating different data types and extracting complex patterns accurately and efficiently from a large volume of data. This course will give an overview of the fundamental concepts, enabling technologies and algorithms in the field of Computational Genomics. The course helps students to understand basic concepts and machine learning based methods in related areas and will enhance the student’s ability in applying them to solve real-world problems. Newly emerging disciplines, i.e. patient stratification, precision medicine and pharmacogenomics will also be discussed in this course. Course Methods and Techniques Prerequisites and co-requisities None Course Coordinator None Name of Lecturers Asist Prof.Dr. VEHBİ ÇAĞRI GÜNGÖR burcu.gungor@agu.edu.tr Assistants None Work Placement(s) No Recommended or Required Reading Resources

 





https://sis.agu.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=74880&lang=en