Faculty of Engineering and Natural Sciences
Department of Genetics and Bioengineering

Code Name Level Year Semester
GBE 336 Genomics Undergraduate 3 Spring
Status Number of ECTS Credits Class Hours Per Week Total Hours Per Semester Language
Area Elective 5 2 + 2 32 English

Instructor Assistant Coordinator
Amina Kurtović Kozarić, Assoc. Prof. Dr. Amina Kurtović Kozarić, Assoc. Prof. Dr.
[email protected] no email

The recent proliferation of genomic data has transformed biology, making previously laborious
and expensive experiments easier and cheaper, enabling new avenues of inquiry, and
fundamentally altering our understanding of biology and medicine. This course will introduce
you to the questions that can be asked and answered with genomic data, and to the
computational tools available to analyze that data. The primary goals are:
• to learn how genomic data are being used to provide new insights throughout biology and
• to become familiar with the tools and databases available for bioinformatics analysis, with an
appreciation of the quantitative concepts that underlie those tools.
• to develop the ability to formulate and investigate genomic research questions, and to
effectively communicate your questions, methods, and results.

  1. Syllabus
  2. Intorduction to Genomics and Proteomics, Classical approach to Genomics
  3. What is cloning
  4. cDNA Libraries
  5. PCR
  6. Seq Clone gene and BLAST
  7. Analysis of gene expression
  8. Genomics analysis
  9. Genomics tools
  10. proteomics tols
  11. Post genomics analysis
  12. Next-generation sequences
  13. Data extraction

  1. Introduction

  1. Mostly used web tools
  2. Learning how to use bioinformatics tools
  3. Genomics tools application
  4. NCBI, USCS,Ensembl
  5. Genomics data research, Methylation, microRNA, somatic mutation data,etc
  6. Clustering and statistical analysis tools
  7. Gene expression analysis
  8. Proteomics structure and 3D view
  9. Proteomics tools and their application
  10. Protein structure and domain fucntions
  11. Combination of Genomics and Proteomics data
  12. Alternatively splicing
  13. RNA seq sequence

  • Lectures
  • Practical Sessions
  • Excersises
  • Presentation
  • Project
  • Assignments
Description (%)
Method Quantity Percentage (%)
Midterm Exam(s)30
Final Exam140
participation 10
Total: 90
Learning outcomes
  • Lectures will introduce some of the common techniques and algorithms used in genomic analysis, including sequence alignment, BLAST, gene expression profiling, and prediction of protein structure and gene function.
  • Throughout the course, we will explore how these techniques, and genomic data in general have been used to explore topics such as evolutionary history, genetic causes of disease, the cancer biology, and microbial ecology (metagenomics
  • The integration of information from diverse sources
  • Using all genomics data and analysis the result.
  • There is no assumption of previous experience beyond knowing how to move files around and use the web, word processors and spreadsheets
  • From Genes to Genomes Concepts and Applications of DNA Technology 3 edition

ECTS (Allocated based on student) WORKLOAD
Activities Quantity Duration (Hour) Total Work Load
Lecture (14 weeks x Lecture hours per week)14228
Laboratory / Practice (14 weeks x Laboratory/Practice hours per week)224
Midterm Examination (1 week) 0
Final Examination(1 week) 0
Preparation for Midterm Examination 0
Preparation for Final Examination5 0
Assignment / Homework/ Project 0
Seminar / Presentation 0
Total Workload: 32
ECTS Credit (Total workload/25): 1