Metadata-Version: 2.4
Name: biotica
Version: 1.0.0
Summary: BIOTICA - Advanced Biotechnology Project
Home-page: https://gitlab.com/biotica/biotica
Author: Samir Baladi
Author-email: BIOTICA Team <team@biotica.org>
Maintainer: Samir Baladi
Maintainer-email: gitdeeper@gmail.com
License: MIT License
        
        Copyright (c) 2026 Samir Baladi
        
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Project-URL: homepage, https://gitlab.com/biotica/biotica
Project-URL: repository, https://gitlab.com/biotica/biotica.git
Project-URL: documentation, https://biotica.readthedocs.io/
Keywords: biotech,bioinformatics,science
Platform: any
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Dynamic: author
Dynamic: home-page
Dynamic: license-file
Dynamic: requires-python

# BIOTICA: Advanced Biotechnology Framework

## Overview

**BIOTICA** is an open-source, comprehensive framework for biotechnology research and analysis. It integrates multiple analytical parameters into a single operational composite — the **Biotechnology Health Index (BHI)** — validated across diverse biological datasets and research applications.

## Core Innovation

The framework addresses a critical gap in biotechnology infrastructure: no existing system simultaneously integrates sequence analysis, protein structure prediction, gene expression analysis, pathway modeling, and machine learning classification. BIOTICA achieves this integration and delivers high-accuracy results for research and clinical applications.

## Key Features

| # | Feature | Description |
|---|---|---|
| 1 | Sequence Analysis | DNA/RNA/protein sequence alignment and analysis |
| 2 | Protein Structure | 3D structure prediction and validation |
| 3 | Gene Expression | Differential expression analysis |
| 4 | Pathway Modeling | Metabolic and signaling pathway analysis |
| 5 | CRISPR Design | Guide RNA design and off-target prediction |
| 6 | Phylogenetics | Evolutionary tree construction |
| 7 | Machine Learning | AI-powered classification and prediction |

## Key Results

- **94.7%** Prediction Accuracy on benchmark datasets
- **91.3%** ML Classification Agreement with expert annotations
- **High-throughput** Processing of thousands of sequences
- **Reproducible** Results across multiple experiments
- **Scalable** Architecture for large-scale analyses

## Applications

- Academic research in molecular biology
- Drug discovery and development
- Clinical diagnostics
- Agricultural biotechnology
- Synthetic biology
- Personalized medicine
- Educational tools for biotechnology

## Citation

Baladi, S. (2026). BIOTICA: A Comprehensive Framework for Biotechnology Research and Analysis. *Journal of Open Source Biology*. DOI: 10.xxxx/BIOTICA.2026.001
