Proposal Title
Designing an in inquiry-based semester theme that integrates data science and bioinformatics methods
Session Type
Presentation
Room
Somerville House, room 3315
Start Date
14-7-2023 11:00 AM
End Date
14-7-2023 11:20 AM
Keywords
bioinformatics, biology, data science, life science, R language, BLAST, Python
Primary Threads
Education Technologies and Innovative Resources
Abstract
With an exponential growth in life science research data, familiarity with bioinformatics has become an exciting as well as a popular skill set both in industry and academia. To increase students’ competencies and to get them familiarized with data science professions, we implemented a set of bioinformatic exercises into a capstone course of a graduate program. Bioinformatic exercises were designed to teach students to navigate bioinformatic databases—such as ExPASy, GenBank™, NiceZyme, and BRENDA—use built-in tools, analyze data, and perform R and Python programming. The skillsets imparted by this research-focused bioinformatic pedagogical approach will empower students to be able to leverage this knowledge for their future endeavors in the bioinformatics field. The presentation comprises a brief intro on the motivation behind the exercises, the semester theme context in which they were developed, and their impact on students’ learning. This research was approved by our institutional research ethics board.
Elements of Engagement
This presentation aims to enable participants to identify a semester theme and develop a lesson plan as well as assessment methods to integrate into their own courses.
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Designing an in inquiry-based semester theme that integrates data science and bioinformatics methods
Somerville House, room 3315
With an exponential growth in life science research data, familiarity with bioinformatics has become an exciting as well as a popular skill set both in industry and academia. To increase students’ competencies and to get them familiarized with data science professions, we implemented a set of bioinformatic exercises into a capstone course of a graduate program. Bioinformatic exercises were designed to teach students to navigate bioinformatic databases—such as ExPASy, GenBank™, NiceZyme, and BRENDA—use built-in tools, analyze data, and perform R and Python programming. The skillsets imparted by this research-focused bioinformatic pedagogical approach will empower students to be able to leverage this knowledge for their future endeavors in the bioinformatics field. The presentation comprises a brief intro on the motivation behind the exercises, the semester theme context in which they were developed, and their impact on students’ learning. This research was approved by our institutional research ethics board.