The Introduction to Bioinformatics Algorithms virtual lab is an interactive online platform designed to provide students with a solid foundation in the computational techniques used in modern bioinformatics. This lab offers a unique blend of theoretical understanding and hands-on experience with biological data, enabling learners to explore how algorithms are applied to solve real-world problems in biology and biotechnology.
Through a series of carefully structured experiments, students will engage with fundamental bioinformatics algorithms such as phylogenetic tree construction (Fitch-Margoliash, Neighbor-Joining), RNA secondary structure prediction (Nussinov and Zuker algorithms), sequence assembly (De Bruijn graphs), gene prediction (Viterbi algorithm), and peptide sequencing (Branch-and-Bound). These modules are designed to build both conceptual clarity and practical skills.
This virtual lab serves as an ideal learning tool for undergraduate and postgraduate students from disciplines like biotechnology, bioinformatics, microbiology, and computational biology. It supports tutor-independent learning and introduces basic programming skills relevant to analyzing and interpreting biological data.
By the end of the course, students will be equipped to apply bioinformatics algorithms confidently and will be better prepared for experimental research or advanced study in interdisciplinary fields that combine biology, computer science, and data analysis