NumPy for Numerical Data - Tutorial Lecture 5 - Python for Biological Data Analysis

Welcome back to Bioinformatics Insights! In this tutorial, we explore the essential toolkit for scientific computing in Python—NumPy—with a focus on numerical data from biological experiments.

Whether you're analyzing fluorescence intensities, growth curves, or molecular measurements, this video will walk you through:

📊 Arrays for storing experimental measurements ➕ Mathematical operations on biological datasets 📈 Statistical calculations: mean, median, standard deviation

All demonstrated in Google Colab, making it easy to follow and apply to your own bioinformatics workflows. This is a must-watch for students and researchers working in computational biology, life sciences, and biotech.

💡 By the end of this session, you'll be equipped to handle numerical data efficiently and perform key statistical analyses using NumPy.

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