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https://github.com/md-emon-hasan/2-simple-bioinformatics-dna-ml-app
A simple bioinformatics application for DNA sequence analysis using machine learning techniques, implemented in Python.
https://github.com/md-emon-hasan/2-simple-bioinformatics-dna-ml-app
bioinformatics data-science data-visualization deployment dna-sequences dna-sequencing supervised-machine-learning
Last synced: 4 days ago
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A simple bioinformatics application for DNA sequence analysis using machine learning techniques, implemented in Python.
- Host: GitHub
- URL: https://github.com/md-emon-hasan/2-simple-bioinformatics-dna-ml-app
- Owner: Md-Emon-Hasan
- License: apache-2.0
- Created: 2024-01-22T17:14:35.000Z (10 months ago)
- Default Branch: master
- Last Pushed: 2024-08-03T11:28:57.000Z (4 months ago)
- Last Synced: 2024-08-03T12:37:42.874Z (4 months ago)
- Topics: bioinformatics, data-science, data-visualization, deployment, dna-sequences, dna-sequencing, supervised-machine-learning
- Language: Python
- Homepage: https://simple-bioinformatics-dna-ml-apps.onrender.com
- Size: 187 KB
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Machine Learning Project: Simple Bioinformatics DNA Analysis App
Welcome to the **Simple Bioinformatics DNA Analysis App** machine learning project repository! This project focuses on analyzing DNA sequences using machine learning techniques to provide insights and predictions related to bioinformatics.
## 📋 Contents
- [Introduction](#introduction)
- [Why This Project](#why-this-project)
- [Dataset](#dataset)
- [Features](#features)
- [Setup and Installation](#setup-and-installation)
- [Demo](#demo)
- [Contributing](#contributing)
- [Challenges Faced](#challenges-faced)
- [Lessons Learned](#lessons-learned)
- [License](#license)
- [Contact](#contact)
---
## 📖 Introduction
This repository contains a machine learning project focused on analyzing DNA sequences for various bioinformatics applications. It includes data preprocessing, model development, evaluation, and a simple web-based application for user interaction.
---
## 🎯 Why This Project
The primary motivation behind creating this project is to leverage machine learning for analyzing and interpreting DNA sequences, which can assist in biological research, disease diagnostics, and genetic engineering.
---
## 📊 Dataset
The dataset used for this project contains DNA sequences with associated biological annotations and labels. It is essential for training the models and validating their predictions.
---
## 🌟 Features
- **Data Preprocessing:** Cleaning and encoding DNA sequences for model compatibility.
- **Model Development:** Implementing machine learning models for DNA sequence analysis and classification.
- **Model Evaluation:** Assessing model performance using metrics such as accuracy, precision, and recall.
- **Deployment:** Developing a user-friendly web application for visualizing DNA sequence analysis results.
---
## 🚀 Setup and Installation
To run this project locally, follow these steps:
1. Clone the repository:
```bash
git clone https://github.com/Md-Emon-Hasan/2-Simple-Bioinformatics-Dna-ML-App.git
```
2. Navigate to the project directory:
```bash
cd 2-Simple-Bioinformatics-Dna-ML-App
```
3. Install the required dependencies:
```bash
pip install -r requirements.txt
```
4. Run the web application:
```bash
python app.py
```
5. Open your web browser and go to `http://localhost:5000` to interact with the app.
---
## 🌐 Demo
Explore the live demo of the project [here](https://simple-bioinformatics-dna-ml-apps.onrender.com)
---
## 🤝 Contributing
Contributions to enhance or expand the project are welcome! Here's how you can contribute:
1. **Fork the repository.**
2. **Create a new branch:**
```bash
git checkout -b feature/new-feature
```
3. **Make your changes:**
- Implement new features, improve model performance, or enhance user interface.
4. **Commit your changes:**
```bash
git commit -am 'Add a new feature or update'
```
5. **Push to the branch:**
```bash
git push origin feature/new-feature
```
6. **Submit a pull request.**
---
## 🛠️ Challenges Faced
During the development of this project, the following challenges were encountered:
- Handling large-scale DNA sequence datasets efficiently.
- Selecting and fine-tuning appropriate machine learning models for sequence analysis.
- Ensuring the interpretability and reliability of model predictions in bioinformatics contexts.
---
## 📚 Lessons Learned
Key lessons learned from this project include:
- Importance of domain knowledge in preprocessing biological data.
- Application of deep learning techniques for sequence analysis and classification.
- Considerations for deploying machine learning applications in bioinformatics.
---
## 📄 License
This project is licensed under the Apache License 2.0. See the [LICENSE](LICENSE) file for more details.
---
## 📬 Contact
- **Email:** [[email protected]](mailto:[email protected])
- **WhatsApp:** [+8801834363533](https://wa.me/8801834363533)
- **GitHub:** [Md-Emon-Hasan](https://github.com/Md-Emon-Hasan)
- **LinkedIn:** [Md Emon Hasan](https://www.linkedin.com/in/md-emon-hasan)
- **Facebook:** [Md Emon Hasan](https://www.facebook.com/mdemon.hasan2001/)
Feel free to reach out for any questions or feedback regarding the project!
---
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