Metadata-Version: 2.4
Name: pamd_biology
Version: 0.1.0
Summary: Massive standard property databases for engineering and science in PyAct.
Home-page: https://github.com/Abstergo2003/PyAct
Author: Abstergo2003
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown
Dynamic: author
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: requires-python
Dynamic: summary

<div align="center">
  <h1>🧬 PyAct Catalogue: Biology</h1>
  <p><b>The standard property database for life sciences and biochemistry.</b></p>
</div>

**pamd-biology** is a standalone, installable knowledge base designed to plug directly into the PyAct engine. It contains standardized biological, cellular, and biochemical properties wrapped perfectly in PyAct's `Unit` class. 

Whether you are calculating enzyme kinetics, molecular weights, or cellular volumes, this package provides instant access to standard life science data without needing to look it up.

## 🚀 Installation

Install it directly from PyPI:
```bash
pip install pamd-biology
```
*(Note: Installing this package will automatically install `pyact-cli` and its core `Unit` library as a dependency.)*

## 📖 What's Included?

This package contains standard biological datasets tailored for biochemistry and cellular biology calculations.

### 1. Macromolecules
* **`AminoAcids`**: The 20 standard proteinogenic amino acids with their molecular weights (`[Da]`), isoelectric points (`pI`), and Kyte-Doolittle hydropathy indices.
* **`NucleicBases`**: Molecular weights for the standard DNA and RNA free bases (Adenine, Thymine, Cytosine, Guanine, Uracil).
* **`MacromoleculeDensities`**: Average buoyant densities (`[g/cm3]`) and partial specific volumes for proteins, DNA, RNA, lipids, and carbohydrates (essential for ultracentrifugation).

### 2. Cellular Biology & Organisms
* **`TypicalCells`**: Standard cell volumes (`[um3]`), typical mass (`[pg]`), and diameters for *E. coli*, Yeast, Red Blood Cells, and HeLa cells.
* **`OrganismGenomes`**: Genome sizes (`[bp]`), chromosome counts, and estimated gene counts for model organisms (E. coli, Yeast, C. elegans, Drosophila, and Humans).

### 3. Biochemistry & Kinetics
* **`EnzymeKinetics`**: Typical Michaelis-Menten constants ($K_m$) and turnover numbers ($k_{cat}$) for classic reference enzymes (like Catalase, Hexokinase, Acetylcholinesterase).
* **`Bioenergetics`**: Standard free energy of hydrolysis ($\Delta G^\circ$) for massive energy carriers like ATP, ADP, and Phosphoenolpyruvate.

### 4. Clinical Baselines
* **`HumanBloodParameters`**: Clinical adult human blood baselines including pH ranges, osmolarity, fasting glucose, and hemoglobin levels.

## 🛠️ Usage Example

Import any biological database directly into your PyAct `.pamd` context and perform instant math. Because every value is a `Unit` object, calculations are completely seamless.

```python
from pamd_biology.AminoAcids import AminoAcids
from pamd_biology.EnzymeKinetics import TypicalEnzymes
from pamd_biology.unit import Unit

def context():
    # Fetch standard values
    valine_mass = AminoAcids().Valine["MW_Da"]
    kcat_catalase = TypicalEnzymes().Catalase["kcat_1_s"]
    
    return {
        "valine_weight": valine_mass,
        "catalase_turnover": kcat_catalase
    }
```
