Data Science & Bioinformatics Portfolio

Juan Ochoteco Asensio

This repository serves as a professional portfolio showcasing projects in data analysis, epidemiological modeling, and machine learning. As a bioinformatician, I focus on transforming raw data into actionable insights through rigorous statistical methods, reproducible workflows, and interactive visualizations.

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🚀 Key Projects

1. COVID-19 Epidemiological Analysis

A comprehensive suite of tools for analyzing global pandemic trends using data from Our World in Data (OWID).

• Dynamic Bar Chart Races: High-quality animations (YouTube-style) depicting the spread of cases per million.
• Vaccination Impact Modeling: Statistical analysis of the correlation between vaccination rates and mortality.
• Excess Mortality Analysis: Comparison of confirmed deaths vs. absolute excess mortality to understand the pandemic's true impact.
• Interactive Dashboard: A Shiny application for real-time data exploration and country-specific trend analysis.

2. Machine Learning & Predictive Modeling

Implementation of various ML algorithms and deep learning architectures.

• LSTM Time-Series Forecasting: Neural networks (Keras/TensorFlow) designed to predict future COVID-19 case trends.
• Regression & Classification: Tutorials and custom implementations for predictive analysis.

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📂 Project Structure

• scripts/: Modular R and Python logic.
  • covid19/: Epidemiological analysis and plotting scripts.
  • machine-learning/: Deep learning (LSTM) and traditional ML experiments.
  • apps/: Full applications, including the Shiny Interactive Explorer.
  • utils/: Shared helper functions and data processing utilities.
• results/: Generated visualizations, animations, and analysis reports.
• data/: (Placeholder) Local data storage and raw data descriptions.
• docs/: Technical documentation and project deep-dives.
• renv/: Full environment reproducibility using the R package manager.

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🛠 Tech Stack

• Language: R (Primary), Python.
• Frameworks: Keras, TensorFlow, Shiny.
• Visualization: ggplot2, gganimate, Plotly, ggstream, Viridis.
• Reproducibility: renv, Git.

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📈 How to Use

1. Clone the repository:

   https://github.com/jochotecoa/Own-Projects.git

2. Restore the environment: Open the .Rproj file in RStudio. renv should automatically prompt you to restore packages. If not, run:

   renv::restore()

3. Run the Dashboard:

   shiny::runApp("scripts/apps/covid19-dashboard")

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📝 License

This project is licensed under the Apache License 2.0.