https://github.com/armandfs/genom-comp-fp
This project leverages computational techniques to analyze genomic data from eukaryotic cells. The program calculates open reading frames (ORFs) from FASTA files, outputs genomic data, sequences, statistics, and includes a Hidden Markov Model (HMM) with an interactive GUI built using `ipywidgets`.
https://github.com/armandfs/genom-comp-fp
Last synced: 7 months ago
JSON representation
This project leverages computational techniques to analyze genomic data from eukaryotic cells. The program calculates open reading frames (ORFs) from FASTA files, outputs genomic data, sequences, statistics, and includes a Hidden Markov Model (HMM) with an interactive GUI built using `ipywidgets`.
- Host: GitHub
- URL: https://github.com/armandfs/genom-comp-fp
- Owner: ArmandFS
- License: unlicense
- Created: 2023-12-05T04:01:06.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2024-07-17T04:48:52.000Z (almost 2 years ago)
- Last Synced: 2025-01-28T23:12:15.360Z (over 1 year ago)
- Language: Jupyter Notebook
- Homepage:
- Size: 483 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# 🌟 Genomic Computation Final Project 🌟
Welcome to my **Genomic Computation Final Project** repository! This project leverages computational techniques to analyze genomic data from eukaryotic cells. The program calculates open reading frames (ORFs) from FASTA files, outputs genomic data, sequences, statistics, and includes a Hidden Markov Model (HMM) with an interactive GUI built using `ipywidgets`.
## 🧬 Introduction 🧬
Genomic computation combines biology and computational methods to provide deep insights into genomic data. This project aims to:
- Calculate open reading frames (ORFs) from eukaryotic cell genomic data.
- Output comprehensive genomic data, sequences, and statistics.
- Utilize a Hidden Markov Model (HMM) for detailed DNA sequence analysis.
- Provide an intuitive GUI with `ipywidgets` for user interaction.
## ✨ Features
- **Open Reading Frame Calculation**: Identify and extract ORFs from eukaryotic cell genomic data.
- **Hidden Markov Model (HMM)**: Advanced DNA sequence analysis using HMM.
- **Interactive GUI**: User-friendly interface powered by `ipywidgets`.
- **Detailed Reports**: Generate and view genomic data, sequences, and statistical analysis.
## 🎉 Example
1. **Upload a FASTA file**:
- Click on the "Upload" button in the GUI and select your FASTA file.
2. **Calculate ORFs**:
- Click on the "Calculate ORFs" button to process the uploaded file.
3. **Analyze with HMM**:
- Click on the "Run HMM Analysis" button to analyze the sequences.
4. **View Results**:
- Results, including genomic data, sequences, and statistics, will be displayed in the GUI.
## 🗂️ Project Structure
```plaintext
genom-comp-fp/
│
├── data/ # Sample data files
├── src/ # Source code
│ ├── orf_calculation.py # ORF calculation module
│ ├── hmm_analysis.py # HMM analysis module
│ ├── gui.py # GUI module using ipywidgets
│ └── main.py # Main script
├── tests/ # Test files
├── README.md # This README file
├── requirements.txt # Python dependencies
```