🧬 VAXINTAIC — Vaccine Intelligence for Antigenic Insight and Construction

VAXINTAIC is an AI-driven computational bioinformatics platform designed to analyze viral genomic data, identify conserved antigenic regions, and evaluate candidate vaccine constructs using automated pipelines and machine learning.

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🚀 Overview

VAXINTAIC provides an end-to-end system that transforms raw viral sequence data into ranked vaccine candidate insights through:

• Sequence acquisition and preprocessing
• Multiple sequence alignment and diversity analysis
• Epitope prediction and ranking
• Synthetic construct simulation (mRNA-level)
• Machine learning-based efficacy prediction
• Interactive dashboard visualization

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🧠 System Architecture

External Sequence Data
        ↓
[01] Sequence Fetching
        ↓
[02] Alignment & Processing
        ↓
[03] Epitope Prediction
        ↓
[04] Epitope Ranking
        ↓
[05] Construct Design
        ↓
[06] Structural Modeling
        ↓
[07] AI Efficacy Prediction
        ↓
[08] Reports & Storage
        ↓
[Dashboard Visualization]

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📂 Project Structure

vaxintaic/
│
├── pipeline/                 # Core computational pipeline
│   ├── 01_fetch_sequences.py
│   ├── 02_align_sequences.py
│   ├── 03_epitope_prediction.py
│   ├── 04_epitope_ranking.py
│   ├── 05_mrna_design.py
│   ├── 06_nanoparticle_model.py
│   ├── 07_efficacy_predictor.py
│   ├── 08_generate_report.py
│   ├── 09_diversity_analysis.py
│   ├── 10_immunogenicity_score.py
│   ├── 11_codon_adaptation.py
│   ├── 12_efficacy_predictor_v2.py
│   └── 13_generate_advanced_report.py
│
├── dashboard/               # Streamlit dashboard
│   ├── app.py
│   ├── part1_overview.py
│   ├── part2_epitope.py
│   ├── part3_diversity.py
│   └── part4_reports.py
│
├── data/                    # Generated outputs
│   ├── sequences/
│   ├── alignments/
│   ├── epitopes/
│   ├── candidates/
│   ├── mrna/
│   ├── models/
│   ├── analysis/
│   └── reports/
│
├── config/                  # Configuration files
├── docs/                    # Images/screenshots
│
├── run_vaxintaic_full.py    # Master pipeline controller
├── requirements.txt
├── README.md
└── .gitignore

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⚙️ Installation Guide

1. Clone Repository

git clone https://github.com/YOUR_USERNAME/vaxintaic.git
cd vaxintaic

2. Create Virtual Environment

python3 -m venv venv
source venv/bin/activate

3. Install Dependencies

pip install -r requirements.txt

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▶️ Running the Pipeline

python run_vaxintaic_full.py

This executes all pipeline stages sequentially:

• Sequence fetching
• Alignment
• Epitope prediction
• Ranking
• Construct design
• ML prediction
• Report generation

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🌐 Running the Dashboard

streamlit run dashboard/app.py

Open in browser:

http://localhost:8501

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📊 Dashboard Features

• 🧭 Pipeline overview and metrics
• 📈 Construct performance analytics
• 🧫 Epitope visualization
• 🧬 Diversity and alignment insights
• 📄 Report and log viewer
• 🧠 JSON construct intelligence explorer

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🧬 Pipeline Inspection Guide

Inspect Epitope Prediction

nano pipeline/03_epitope_prediction.py

Key logic:

• Sliding window peptide scanning
• Immunogenic scoring

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Inspect mRNA Design

nano pipeline/05_mrna_design.py

Key logic:

• Construct assembly
• Codon optimization (CAI, GC%)

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Inspect AI Model

nano pipeline/07_efficacy_predictor.py

Features used:

• GC content
• Codon adaptation index
• Stability index
• Immunogenicity

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🗄️ Database (MySQL)

VAXINTAIC uses MySQL for structured storage.

Main Tables

pipeline_metrics_v3

Tracks pipeline runs:

timestamp_utc
num_sequences
construct_count
duration_sec

construct_intelligence_v3

Stores construct-level intelligence:

construct_id
prrsv_type
timestamp_utc
data (JSON)

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📊 Data Flow

Pipeline Scripts
      ↓
CSV / FASTA Outputs
      ↓
MySQL Database
      ↓
Streamlit Dashboard

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🌍 Deployment

Local Deployment

streamlit run dashboard/app.py --server.port 8090

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Server Deployment (Example)

http://YOUR_SERVER_IP:8090

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Live System (Example)

https://prrsv-vaccine.aiconceptlimited.com.ng/

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🧠 Technologies Used

• Python
• Pandas / NumPy
• BioPython
• Scikit-learn
• Streamlit
• Plotly
• MySQL

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⚠️ Disclaimer

This platform is intended for computational research, simulation, and educational purposes only.

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👨‍🔬 Author

Abubakar VAXINTAIC — AI for Vaccine Intelligence