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Introduction to Bioinformatics and Computational Genomics

CMPE 484

Instructor: Arzucan Özgür, Department of Computer Engineering, BM 18, arzucan.ozgur@boun.edu.tr

Semester: Spring 2022

Credits: (3+0+2) 4 ECTS 6

Course Description

Advances in technology has led to the generation of huge amount of biological and genomics data, the analysis of which results in challenges as well as in opportunities for a better understanding of the biological processes underling life and health. This course will provide a basic understanding of the fundamental algorithms for genomic and biological data analyses.


Course Objectives

  • Understand the fundamentals of the fields of bioinformatics and computational genomics.
  • Learn the main algorithms for processing and analysing biological/genomics data.
  • Gain knowledge about biological/genomics databases and resources.
  • Design and develop computational methods for processing/analysing real world biological/genomics data.

Prerequisites

Medium level programming skills in the Python programming language, background on data structures and algorithms.


Course Web Site

We will use the Moodle Course Management System for lecture notes, announcements, grades, as well as assignments and project submissions: https://moodle.boun.edu.tr.

You are expected to check the course web site for announcements regularly.


Reference Books (Optional)

  1. Genome-scale algorithm design

    • Authors: Mäkinen, V., Belazzougui, D., Cunial, F., & Tomescu, A. I.
    • Publisher: Cambridge University Press, 2015
    • Website: http://www.genome-scale.info

  2. Bioinformatics and functional genomics

    • Author: Pevsner, J.
    • Publisher: John Wiley & Sons, 2015

  3. Bioinformatics Algorithms: An Active Learning Approach

    • Authors: P. Compeau, P. Pevzner
    • Edition: 3rd Edition, 2018
    • Note: Volume 1 and 2 of the Second Edition is also fine
    • Supplementary website: http://bioinformaticsalgorithms.com

Tentative List of Topics

  • Basic Overview of Biology
  • Overview of Biological/Genomics Databases and Resources
  • Pairwise and Multiple Sequence Alignment
  • Heuristic Algorithms for Sequence Search
  • Building Phylogenetic Trees
  • Gene Expression Analysis
  • Genome Sequencing and Assembly
  • Analysis of Next-Generation Sequencing Data
  • Gene Finding and Motif Discovery

Grading

  • Assignments: 55%
  • Tool/Resource presentation: 15%
  • Final Exam: 30%
Download Syllabus Course Materials