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…

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…

Lipidomics is a discipline that focuses on the identification and quantification of lipids. Although a part of the larger omics field, lipidomics requires specific approaches for the analysis and biological interpretation of datasets. This article presents a series of activities for introducing undergraduate microbiology students to lipidomic…

The study and analysis of enzymatic reactions are essential for characterizing various biological systems. As part of these procedures, it is important to understand how to quantify the biological activity of these proteins in terms of enzymatic activity. This work proposes a general equation for determining enzymatic activity based on…

The ability to analyze large data sets ("Big Data") is an increasingly important skill in modern science. In Biochemistry, the increased volume and velocity of data is particularly evident in the rapid expansion of biological databases. We present a modular bioinformatics course to survey the analysis of genomic data for advanced…

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…

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…

Enzymes are nature's catalysts, mediating chemical processes in living systems. The study of enzyme function and mechanism includes defining the maximum catalytic rate and affinity for substrate/s (among other factors), referred to as enzyme kinetics. Enzyme kinetics is a staple of biochemistry curricula and other disciplines, from molecular and…

With rapid development of sequencing technology and the continuous accumulation of biological big data, people who are capable of using bioinformatic skills to analyze omics data and work out biological problems are urgently needed in the workforce, which highlights the importance of developing bioinformatics skills early in the undergraduate…

This article reports a session from the virtual international 2021 IUBMB/ASBMB workshop, "Teaching Science on Big Data." The awareness of using publicly available research data sets for undergraduate training is low in certain parts of the world. Final year projects always revolve around wet-lab based projects. The challenges occur…

Glycosylation is a biologically significant post-translational modification (PTM) of proteins that involves the covalent attachment of a sugar molecule (a glycan) to a peptide sequence, resulting in the formation of glycoproteins. Glycomics and glycoproteomics involve the complete mapping of glycans of a cell, tissue, or organism.…

One significant impact of the COVID-19 pandemic for educators in forensic science was adapting what is traditionally a very applied field to a virtual learning environment. Because of this, science classes with a practical laboratory component had to implement significant adjustments to ensure that student learning objectives were still met,…

The final year of a biochemistry degree is usually a time to experience research. However, laboratory-based research projects were not possible during COVID-19. Instead, we used open datasets to provide computational research projects in metagenomics to biochemistry undergraduates (80 students with limited computing experience). We aimed to give…

To best prepare students for the real-world research environment, key skills, including experimental design, data analysis, communication of results, and critical thinking, should be key components of undergraduate science courses. Furthermore, the impact of the COVID-19 pandemic on in-person teaching has resulted in a need to develop courses that…

Integrating the use of large datasets into our teaching provides critical and unique opportunities to build students' skills and conceptual knowledge. Here, we discuss the core components needed to develop effective activities based on large datasets, which align with the 5E learning cycle. Data-based activities should be structured around a…