https://github.com/bibymaths/python_snippets

A collection of Python scripts for bioinformatics data analysis, including tools for transcription counts, nucleotide composition, and protein sequence evaluation.
https://github.com/bibymaths/python_snippets

amino-acid-scoring bioinformatics data-analysis fasta-generation mathematical-evaluation nucleotide-analysis protein-sequence-analysis transcription-counts

Last synced: 2 days ago
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A collection of Python scripts for bioinformatics data analysis, including tools for transcription counts, nucleotide composition, and protein sequence evaluation.

• Host: GitHub
• URL: https://github.com/bibymaths/python_snippets
• Owner: bibymaths
• License: mit
• Created: 2025-01-18T21:44:47.000Z (11 days ago)
• Default Branch: main
• Last Pushed: 2025-01-18T21:50:20.000Z (11 days ago)
• Last Synced: 2025-01-18T22:26:47.430Z (11 days ago)
• Topics: amino-acid-scoring, bioinformatics, data-analysis, fasta-generation, mathematical-evaluation, nucleotide-analysis, protein-sequence-analysis, transcription-counts
• Language: Python
• Homepage:
• Size: 0 Bytes
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Bioinformatics Tools and Scripts

This repository contains various Python scripts developed for bioinformatics research, with a focus on data analysis, evaluation, and transformation. These tools cater to different aspects of biological data processing, including transcription counts, nucleotide evaluation, and protein-based analyses.

## Repository Contents

1. **`aa_score_ranking.py`**: Evaluates amino acid scores and ranks them based on specific criteria.

2. **`mathematical_operators_eval.py`**: Performs mathematical evaluations, focusing on specific operations for bioinformatics datasets.

3. **`nucleotide_count.py`**: Counts and analyzes nucleotide compositions in DNA sequences.

4. **`aa_charge_to_fasta.py`**: Converts amino acid charge data into FASTA format for downstream analysis.

5. **`transcription_counts.py`**: Processes transcription count data for gene expression studies.

## Usage

Each script is self-contained and focuses on a specific data processing task. To use these scripts:

1. Clone this repository to your local machine:

   ```bash

   git clone 

   ```

2. Navigate to the script of interest and execute it in a Python environment:

   ```bash

   python .py

   ```

## Prerequisites

- Python 3.8 or higher

- Required Python packages (can be installed using `requirements.txt` if provided)

## Key Features

- **Modular Design**: Scripts are independent, allowing focused use based on task requirements.

- **Bioinformatics Focus**: Tailored for common bioinformatics data transformations and evaluations.

- **Extensibility**: Easy to adapt and integrate into larger workflows.

## Contribution

Contributions are welcome! If you'd like to improve existing scripts or add new functionalities, please fork the repository, make your changes, and submit a pull request.