SYBB 412

Programming for Bioinformatics

Bioinformatics Programming with SYBB 412

SYBB 412: Programming for Bioinformatics is an essential course offered in Spring at Case Western Reserve University. This course is designed to equip students with the programming skills necessary for bioinformatics analysis, focusing primarily on the R programming language. This course was developed by Dr. Gürkan Bebek to provide a comprehensive introduction to bioinformatics programming.

Course Overview

SYBB 412 is a 3-credit course that introduces students to bioinformatics analysis and programming in R. This course is suitable for both beginners and advanced programmers, providing hands-on experience with bioinformatics software, R packages, and functions tailored for bioinformatics applications.

Instructor Information

  • Instructor: Gürkan Bebek, Ph.D., M.S.
  • Office: 10900 Euclid Ave. BRB 921, Cleveland, OH 44106-4988
  • Phone: (216) 368-4541
  • Email: gurkan.bebek@case.edu

Prerequisites

SYBB 402: Introduction to Scientific Computing SYBB 411: Technologies, Data Integration and Translational Approaches in Bioinformatics

Students can seek waivers based on their past classes.

Key Learning Objectives

  • Data Analysis in Bioinformatics: Understand and utilize bioinformatics tools and models to build pipelines for interpreting and analyzing large datasets.
  • Programming Skills: Develop software solutions to bioinformatics problems, manipulate data files, and use open-source bioinformatics platforms such as R, Cytoscape, and Crosstalker.
  • Practical Application: Complete -omics data analysis, including differential gene expression and proteomics, and produce reproducible research.

Course Structure

Classes are held on Tuesdays and Thursdays from 2:30 to 3:45 PM. The final exam is scheduled for early May. The course includes lectures, in-class exercises, homework assignments, and a class project.

Required Materials

Students will need access to the following online textbooks, all available for free:

  • “Translational Bioinformatics” (PLoS Computational Biology)
  • “R Programming for Data Science” by Roger D. Peng
  • “R for Data Science (2e)” by Hadley Wickham, Mine Çetinkaya-Rundel, and Garrett Grolemund

Grading Breakdown

  • Assignments: 30%
  • Class Project: 25%
  • Canvas Participation: 5%
  • In-Class Participation: 10%
  • Course Evaluations: 5%
  • Final Exam: 25%

Course Highlights

Throughout the semester, students will explore a variety of topics, including:

  • Reproducible Research: Learn the principles of reproducible computational research and best practices in project management.
  • Microarray and NGS Data Analysis: Gain skills in analyzing high-throughput data and next-generation sequencing data.
  • ** …-seq**: Understand and build large -omic data anysis workflows.
  • Visualization and Data Manipulation: Master data visualization and data cleaning techniques in R.
  • Network Biology: Explore networks and basic network analysis using R.

Why Enroll in SYBB 412?

This course is ideal for students interested in the intersection of biology, technology, and data science. It provides a solid foundation in bioinformatics programming and practical skills that are highly valued in today’s data-driven world. Reproducibility is a cornerstone of scientific research, ensuring that results can be consistently replicated by others. In SYBB 412, students will learn the principles of reproducible computational research, including best practices in project management, data management from open-source databases, creating dynamic and reproducible reports, and tracking version control. Whether you’re aiming for a career in bioinformatics or biomedical research, SYBB 412 offers valuable insights and hands-on experience.

For more information, please request the full syllabus via email (available to CWRU students only).