🧬 Eukaryote Neural Net

Modeling eukaryotic genomes using machine learning to identify functional elements like enhancers, introns, and promoter strength.

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🧬 Overview

This project leverages deep learning to parse and predict various genomic features within eukaryotic DNA sequences. By training on established genomic datasets, these models provide high-accuracy mapping of regulatory and structural elements.

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🚀 Key Features

🧬 Genomic Encoding

Robust scripts for converting raw FASTA or nucleotide sequences into machine-learning-ready formats using one-hot encoding or k-mer embeddings.

🧠 Deep Learning Architectures

Implementation of specialized neural networks (such as CNNs or Transformers) tailored for long-range sequence analysis.

🔍 Predictive Modeling

Dedicated modules for:

• Enhancer Regions: Identifying distal regulatory elements
• Intron/Exon Boundaries: Predicting splice sites and gene structure
• Promoter Strength: Quantifying potential transcriptional activity

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🛠 Installation

To set up the environment and install necessary dependencies, run the following commands in your terminal:

# Clone the repository
git clone https://github.com/helloftroy/eukaryote_neural_net.git

# Navigate to the project directory
cd eukaryote_neural_net

# Install requirements
pip install -r requirements.txt

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💻 Usage

1. Data Preparation

Preprocess your raw genomic data into the required tensor format:

python src/preprocess.py --input data/raw_genome.fasta

2. Training

Train the model using a configuration file:

python src/train.py --config configs/model_v1.yaml

3. Inference

Run predictions on a specific sequence:

python src/predict.py --sequence "ATGCGAT..."

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🧪 Technical Details

• Target Organisms: Eukaryotic genomes (adaptable for model organisms like S. cerevisiae or Arabidopsis)
• Framework: PyTorch
• Evaluation Metrics: Precision-Recall curves, F1-scores, and Mean Squared Error (MSE) for promoter quantification

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⚠️ Notes

This project is a work in progress. Future updates may include support for non-model organisms and expanded regulatory element detection.

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