Welcome to this collection of blogs, designed primarily to help students simplify challenging interdisciplinary topics. The posts are categorized into five sections β Statistics & Machine Learning π΄, Simulated Evolution π’, Programming π΅, Systems Medicine π€, and Epidemiological Modelling π‘. I have tried to include clear explanations and, where applicable, hands-on coding examples with accessible code. Your feedback and suggestions are greatly valued, so feel free to share your thoughts. Thank you for visiting!
Note: For an optimal reading experience, larger screens are recommended.
π΅Introduction to R Graphics - From Basic to High-Quality Plots
π΅The First Course on R β Foundations and Data Structures
π’ The Founder Effect Simulation
π΄Understanding Data Dredging (p-hacking) in Multiple Comparison Tests
π΄A Dynamic Decision Tree for Choosing the Proper Statistical Test
π’Understanding the Roles of Nucleic Acid Substitution Models in Molecular Evolution
π’ When Science Hits a High Note: Craft a Tune From Thy Protein Sequence
π΅Parallel Programming in Biological Data: The R vs Python Showdown
π€A Guided Introduction to Systems Medicine - The Insulin-Glucose Circuit
π’3D Model of DNA Double Helix from X-ray Diffraction Data
π΄Bringing Order to Chaos: An Introduction to Cluster Algorithms in Biology
π΄A Gentle Introduction to Neural Network & Deep Learning
π’Simulating the Red Queen Hypothesis in the Context of Bacteria-Phage Evolutionary Arms Race
π΅A Dive into Dynamic Programming Algorithms in Biology: Needleman-Wunsch and Smith-Waterman
π΄Introduction to Probability Algorithms in Biology - Maximum Likelihood Estimation and Bay's Theorem
π΄From Raw to Refined: Essential Data Transformation Techniques in Biology
π΄The Overfitting Dilemma: Finding Balance in Statistical Insights
π΄Simplifying Complexity: A Step-by-Step Guide to Common Dimensionality Reduction Methods in Biology
π΅ Test Your Skills: A Data Wrangling Knowledge Assessment
π΄DecipheringΒ Normalization in RNA-Seq
π‘Did Lockdowns Truly Help During COVID-19? A Mathematical Dive into the Pandemic Response