# Western Blot Quantification AI Agent Connect

> Quantify protein expression from western blot data using densitometry and statistical analysis.

## Overview
- **Category:** data-analysis
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_4KOvUoSKEHEuudlzLKG9xTF08mY0jXNg52L2l3PM/ai-agent-connect
- **Tags:** western-blot, protein, densitometry, quantification, statistics

## Description

This MCP server provides a complete suite of tools for analyzing western blot results. It allows AI agents to perform background correction using `analyze_band_densities`, normalize protein levels via `normalize_protein_expression`, calculate group-wise changes with `calculate_fold_change`, and determine statistical significance using `evaluate_statistical_significance`. It transforms raw band intensities into meaningful biological insights like fold change and p-values.

## Tools

### analyze_band_densities
Calculates the corrected intensity of protein bands after removing background noise

### calculate_fold_change
Determines the magnitude of change in protein expression between groups

### evaluate_statistical_significance
Assesses whether differences between experimental groups are statistically meaningful

### normalize_protein_expression
Adjusts target protein levels based on loading controls

## Prompt Examples

**Prompt:** 
```
Calculate the corrected intensities for these bands: Band A (raw 150, bg 20) and Band B (raw 80, bg 30).
```

**Response:** 
```
The corrected intensity for Band A is 130 and for Band B is 50.
```

**Prompt:** 
```
What is the fold change for the 'Treated' group compared to the 'Control' group if the Control mean is 1.0 and the Treated mean is 2.5?
```

**Response:** 
```
The fold change for the Treated group is 2.5.
```

**Prompt:** 
```
Is the difference between Group A and Group B significant if the p-value is 0.02?
```

**Response:** 
```
Yes, the difference is statistically significant as the p-value is below the 0.05 threshold.
```

## Frequently Asked Questions

**How do I correct for background noise in my blots?**
You can use the `analyze_band_densities` tool. Provide the raw intensities and the background intensities for each band to get the corrected values.

**How can I account for unequal protein loading?**
Use the `normalize_protein_expression` tool. By providing both your target protein data and your loading control data (like GAPDH or Actin), the tool calculates relative expression.

**Can I compare multiple experimental groups?**
Yes. You can use `calculate_fold_change` to see the magnitude of change relative to a control, and `evaluate_statistical_significance` to check if those differences are statistically meaningful.