Enzymology: Principles & Applications Structure, classification, kinetics (Michaelis-Menten), inhibition. Industrial uses of enzymes (detergents, food, diagnostics). Genomics & Transcriptomics Whole-genome sequencing, RNA-seq basics. Applications in identifying mutations, gene expression profiling.. 🦠 Microbial Biology & Diversity Classification & physiology of bacteria, fungi, viruses, archaea. Beneficial vs. pathogenic microbes, probiotics, and gut microbiota. 🧮 Data Analysis & Computational Biology Introduction to R/Python for biological datasets. Statistical tests, plotting growth curves,interpreting-omics data. 🧬 CRISPR & Genome Editing Basics of CRISPR-Cas9 mechanism. Applications in microbes, plants, humans. Bioinformatics tools to design guide RNAs.. Data Science & Machine Learning in Bioinformatics Basics of supervised vs. unsupervised learning. Case study: Classifying cancer datasets using Python.
