All Tools
Curve Fitting — Nonlinear Regression
Prism-style curve fitting with Levenberg-Marquardt optimization. 9 models including dose-response, enzyme kinetics, and more.
Equation: Y = Bottom + (Top - Bottom) / (1 + 10^((LogEC₅₀ - X)·Hill)) | Parameters: Bottom, Top, LogEC₅₀, HillSlope
Examples:
4-Parameter Logistic (Dose-Response)
⚙️ Customize
Font Size10px
Line Thickness2px
📥 Download
📊 Data Input
💡 Tip: Paste directly from Excel or Google Sheets (Ctrl+V / ⌘V)
| # | X | Y | |
|---|---|---|---|
| 1 | |||
| 2 | |||
| 3 | |||
| 4 | |||
| 5 | |||
| 6 | |||
| 7 | |||
| 8 | |||
| 9 | |||
| 10 | |||
| 11 |
📖 Available Models (GraphPad Prism-style)
Linear Regression:
Y = a + b·XQuadratic (2nd Order Polynomial):
Y = a + b·X + c·X²Cubic (3rd Order Polynomial):
Y = a + b·X + c·X² + d·X³Exponential Growth:
Y = Y₀ · exp(k·X)Exponential Decay (one-phase):
Y = (Y₀ - Plateau) · exp(-k·X) + Plateau4-Parameter Logistic (Dose-Response):
Y = Bottom + (Top - Bottom) / (1 + 10^((LogEC₅₀ - X)·Hill))Michaelis-Menten:
Y = Vmax · X / (Km + X)Gaussian (Bell Curve):
Y = Amp · exp(-(X - μ)² / (2σ²))Power (Allometric):
Y = a · X^bHill Equation (Cooperative Binding):
Y = Bmax · X^n / (Kd^n + X^n)