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Representing DNA for Machine Learning Algorithms: A Primer on One-Hot, Binary, and Integer Encodings
Yash Munnalal Gupta; Satwika Nindya Kirana; Somjit Homchan – Biochemistry and Molecular Biology Education, 2025
This short paper presents an educational approach to teaching three popular methods for encoding DNA sequences: one-hot encoding, binary encoding, and integer encoding. Aimed at bioinformatics and computational biology students, our learning intervention focuses on developing practical skills in implementing these essential techniques for…
Descriptors: Science Instruction, Teaching Methods, Genetics, Molecular Biology
Allbee, Quinn; Barber, Robert – Biochemistry and Molecular Biology Education, 2021
Biology is a data-driven discipline facilitated greatly by computer programming skills. This article describes an introductory experiential programming activity that can be integrated into distance learning environments. Students are asked to develop their own Python programs to identify the nature of alleles linked to disease. This activity…
Descriptors: Genetics, Science Instruction, Programming Languages, Biology
Incorporating Coding into the Classroom: An Important Component of Modern Bioinformatics Instruction
Nichole Orench-Rivera; April Bednarski; Paul Craig; Austin Talbot – Journal of College Science Teaching, 2025
Advancements in computation and machine learning have revolutionized science, enabling researchers to address once insurmountable challenges. Bioinformatics, a field that heavily relies on computer-driven analysis of biological data, has greatly benefited from these developments. However, traditional bioinformatics instruction frequently lacks the…
Descriptors: Coding, Computer Science Education, Integrated Curriculum, Programming
Revelo, Oscar Sanchez; Collazos Ordonez, Cesar Alberto; Redondo, Miguel A.; Ibert Bittencourt Santana Pinto, Ig – IEEE Transactions on Learning Technologies, 2021
The incorporation of collaborative work in the educational field grows day after day, as does the research associated with this topic. One of the most recurring problems faced by teachers who want to employ this learning strategy is the good students' group formation since this task can be complex both conceptually and computationally, especially…
Descriptors: Homogeneous Grouping, Cooperative Learning, Personality Traits, Genetics
Gupta, Yash Munnalal; Kirana, Satwika Nindya; Homchan, Somjit; Tanasarnpaiboon, Supatcharee – Biochemistry and Molecular Biology Education, 2023
The COVID-19 pandemic has forced the Bioinformatics course to switch from on-site teaching to remote learning. This shift has prompted a change in teaching methods and laboratory activities. Students need to have a basic understanding of DNA sequences and how to analyze them using custom scripts. To facilitate learning, we have modified the course…
Descriptors: Programming Languages, Teaching Methods, Computer Software, Genetics
James A. Parejko – Journal of Microbiology & Biology Education, 2024
The current and ongoing challenges brought on by climate change will require future scientists who have hands-on experience using advanced molecular techniques, can work with large data sets, and can make correlations between metadata and microbial diversity. A course-embedded research project can prepare students to answer complex research…
Descriptors: Plants (Botany), Microbiology, Science Instruction, Teaching Methods
Neyhart, Jeffrey L.; Watkins, Eric – Natural Sciences Education, 2020
Basic quantitative and population genetics topics are typically taught in introductory plant breeding courses and are critical for success in upper-level study. Active learning, including simulations and games, may be useful for instruction of these concepts, which rely heavily on theory and may be more challenging for students. The statistical…
Descriptors: Genetics, Active Learning, Teaching Methods, Plants (Botany)
Lin, Yu-Shih; Chang, Yi-Chun; Chu, Chih-Ping – IEEE Transactions on Learning Technologies, 2016
The grouping problem is critical in collaborative learning (CL) because of the complexity and difficulty in adequate grouping, based on various grouping criteria and numerous learners. Previous studies have paid attention to certain research questions, and the consideration for a number of learner characteristics has arisen. Such a multi-objective…
Descriptors: Cooperative Learning, Experimental Groups, Control Groups, Pretests Posttests