Project portfolio

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SARS-CoV-2 variant binding affinity prediction

Tags: Python, Machine Learning, Statistics, Bioinformatics

The binding between the SARS-CoV-2 virus and human receptors represents the first crucial step for cellular entry, where amino acid (AA) changes in the variants could affect their binding affinity significantly. This project brief describes how a convolutional neural network model is built to predict the binding affinity change upon AA changes, and how this model can be applied to both human and animal cases.

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Yelp dataset analysis

Tags: R, Python, Statistics, Tableau, SQL

Yelp’s businesses, reviews, and user data are a subset of its ever-growing database, which is often been chosen as the capstone project for teaching and research purposes. Despite being explored extensively, this dataset is still a good playground for checking knowledge and practicing analysis skills including statistics, programming, and visualization using R or Python.

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Stock price analysis

Tags: Python, Statistics, SQL

Predicting the stock price fluctuation behavior relies on the understanding of its historical patterns. This project covers the construction of a local database, the fundamental statistical analyses of stock prices, and the design of a Markov chain model.