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Craig, Paul A.; Nash, Jessica A.; Crawford, T. Daniel – Biochemistry and Molecular Biology Education, 2022
A programming workshop has been developed for biochemists and molecular biologists to introduce them to the power and flexibility of solving problems with Python. The workshop is designed to move users beyond a "plug-and-play" approach that is based on spreadsheets and web applications in their teaching and research to writing scripts to…
Descriptors: Programming Languages, Biochemistry, Molecular Biology, Data Analysis
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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
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Novak, Walter R. P. – Biochemistry and Molecular Biology Education, 2022
Biochemistry is a data-heavy discipline, yet teaching students to work with large datasets is absent from many undergraduate Biochemistry programs. Ensuring that future generations of students are confident in tackling problems using big data first requires that educators become comfortable teaching big data skills. The activity described herein…
Descriptors: Biochemistry, Data, Workshops, Undergraduate Students
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Friedman, Alon – Biochemistry and Molecular Biology Education, 2022
The R programming language and computing environment is a powerful and common platform used by life science researchers and educators for the analysis of big data. One of the benefits of using R in this context is its ability to visualize the results. Using R to generate visualizations has gained in popularity due to the increased number of R…
Descriptors: Visual Aids, Peer Evaluation, Scoring Rubrics, Programming Languages
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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
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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
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Kaste, Joshua A. M.; Green, Antwan; Shachar-Hill, Yair – Biochemistry and Molecular Biology Education, 2023
The modeling of rates of biochemical reactions--fluxes--in metabolic networks is widely used for both basic biological research and biotechnological applications. A number of different modeling methods have been developed to estimate and predict fluxes, including kinetic and constraint-based (Metabolic Flux Analysis and flux balance analysis)…
Descriptors: Science Instruction, Teaching Methods, Prediction, Metabolism
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Leonardo D. Garma; Nuno S. Osório – Biochemistry and Molecular Biology Education, 2024
Dimensionality reduction techniques are essential in analyzing large 'omics' datasets in biochemistry and molecular biology. Principal component analysis, t-distributed stochastic neighbor embedding, and uniform manifold approximation and projection are commonly used for data visualization. However, these methods can be challenging for students…
Descriptors: Biochemistry, Molecular Biology, Science Instruction, Learning Experience
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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
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Mariano, Diego; Martins, Pedro; Helene Santos, Lucianna; de Melo-?Minardi, Raquel Cardoso – Biochemistry and Molecular Biology Education, 2019
The advent of the high-throughput next-generation sequencing produced a large number of biological data. Knowledge discovery from the huge amount of available biological data requires researchers to develop solid skills in biology and computer science. As the majority of the Bioinformatics professionals are either computer science or life sciences…
Descriptors: Computer Literacy, Computer Science Education, Programming, Biological Sciences
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Tovar, Glomen – Biochemistry and Molecular Biology Education, 2018
A software to calculate the net charge and to predict the isoelectric point (pI) of a polypeptide is developed in this work using the graphical programming language LabVIEW. Through this instrument the net charges of the ionizable residues of the chains of the proteins are calculated at different pH values, tabulated, pI is predicted and an Excel…
Descriptors: Graduate Students, Computer Software, Biochemistry, Scientific Concepts
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Herraez, Angel – Biochemistry and Molecular Biology Education, 2006
Jmol is free, open source software for interactive molecular visualization. Since it is written in the Java[TM] programming language, it is compatible with all major operating systems and, in the applet form, with most modern web browsers. This article summarizes Jmol development and features that make it a valid and promising replacement for…
Descriptors: Programming, Biochemistry, Programming Languages, Physical Sciences