An Interdisciplinary Approach — Effective Ways for Teaching Bioinformatics

IEEE Computer Society Team
Published 02/09/2023
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Interdisciplinary learning for bioinformaticsDue to Next Generation Sequencing (NGS) technology, technological advances in DNA sequencing have revolutionized research in several areas. These areas include, but are not limited to, medicine, genetics, and molecular biology. As another result of this revolution, Bioinformatics as a science was developed to address the computational issues and challenges that often arise due to analyzing the tremendous amounts of data generated by NGS technology. Bioinformatics is a discipline that intertwines computer science, information, and biology networks and possesses the applications and programs needed to run computational activities.

Educators at California State University, Chico, created a pilot, project-based course in Bioinformatics to address the challenge of insufficient interdisciplinary learning methods for the field. Educators understood from the onset that biology students, whether undergraduate or graduate, were not trained in analyzing large datasets. They also knew that computer science students were not trained in biological sciences. As a result of the lack of instruction in both disciplines, each class of students would be deficient as it relates to knowing the full spectrum of the field of Bioinformatics. To be entirely successful, students must learn Bioinformatics inside and out. As a result, educators must ensure their courses encompass all needed components to prepare all classes of students properly.

These educators created a pair of sister courses that introduced biology and computer science students to Bioinformatics separately and in tandem. The two sister courses were “Computer Science Bioinformatics” and “Biology Informatics.” Each of the courses was created to teach computer science students the biological approach and to teach biological science students the computational approach to bioinformatics. Students were given assignments and tasks to determine the effectiveness of the curriculum and preparedness for work in the field of Bioinformatics. The overall goals of the study were to:

  • Provide students with interdisciplinary experience, so they can learn to communicate with professionals in different fields and could appreciate the importance of each member of a skilled team.
  • Introduce students to the current computational problems in biology using NGS data and increase awareness of industry demand for computer scientists with training in bioinformatics.
  • Incorporate professional research into the class curriculum.

Educators evaluated the progress and overall success of each class participating in this study. The results they received entailed whether the study was effective. Educators were able to assess whether the courses provided all the students needed. Some examples of positive student comments are listed below:



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  • “This course was more enjoyable than most others. It is one of my few classes that makes me feel like a college student. It gives me a real world experience. It helps with problem solving, critical thinking and overall knowledge of biology.”
  • “This course was an amazing experience where students were able to collaborate to critically think about how to implement most efficient algorithm to solve a problem.”
  • “I have enjoyed both the algorithm analysis and programming projects. I have also enjoyed and learned a lot by collaborating with the biology students. Please support more courses like this.”

The article “Bioinformatics Sister Courses: An Interdisciplinary Collaborative Learning Framework to Teach Bioinformatics” is filled with essential information and provides high-level insight into the study presented by professors at California State University, Chico. Read the complete article in the Computer Society Digital Library.