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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
Weiss, Charles J. – Biochemistry and Molecular Biology Education, 2022
This article reports a workshop from the 2021 IUBMB/ASBMB Teaching Science with Big Data conference held virtually in June 2021 where participants learned to explore and visualize large quantities of protein PBD data using Jupyter notebooks and the Python programming language. This activity instructs participants using Jupyter notebooks, Python…
Descriptors: Visual Aids, Programming Languages, Data Analysis, Science Instruction
Green, Michael; Chen, Xiaobo – Journal of Chemical Education, 2020
For undergraduate students to be prepared for graduate school and industry, it is imperative that they understand how to merge the theoretical insights gleaned through their undergraduate education with the raw data sets acquired through materials analysis. Thus, the ability to implement data analysis is a vital skill that students should develop.…
Descriptors: Undergraduate Students, Data, Chemistry, Programming Languages
Del Toro, Israel; Dickson, Kimberly; Hakes, Alyssa S.; Newman, Shannon L. – American Biology Teacher, 2022
Increasingly, students training in the biological sciences depend on a proper grounding in biological statistics, data science and experimental design. As biological datasets increase in size and complexity, transparent data management and analytical methods are essential skills for undergraduate biologists. We propose that using the software R…
Descriptors: Undergraduate Students, Biology, Statistics Education, Data Analysis
Hernandez, Rebecca R.; Mayernik, Matthew S.; Murphy-Mariscal, Michelle L.; Allen, Michael F. – BioScience, 2012
Environmental scientists are increasing their capitalization on advancements in technology, computation, and data management. However, the extent of that capitalization is unknown. We analyzed the survey responses of 434 graduate students to evaluate the understanding and use of such advances in the environmental sciences. Two-thirds of the…
Descriptors: Environmental Education, Programming Languages, Graduate Students, Information Science