Fit sigmoidal dose-response curves and report IC50 or EC50 values from your own data.
Upload concentration and response measurements, and SciFigure fits a four-parameter logistic model per compound before drawing a clean, log-scaled curve with replicate error bars for your manuscript.
Upload data and describe the curve you need.
Costs 5 credits. Curve fits, IC50/EC50 values, and statistics are computed from your uploaded data, then drawn as a PNG.
Preview
Aspect ratio: 16:9
These are sample previews. Upload your dataset to generate your own dose-response curve.
Use these examples as starting points for cell viability assays, receptor agonist studies, enzyme inhibition screens, and compound potency comparisons.
Prompt
Based on the uploaded viability_assay.csv file, fit four-parameter logistic curves for Drug A and Drug B on a log10 concentration axis in nM. Show mean ± SD markers for duplicate wells, add dashed IC50 drop lines, and list each IC50 in the legend.
Prompt
Based on the uploaded camp_agonist.csv file with log molar agonist concentrations, fit a stimulatory 4PL curve, show triplicate mean ± SD, mark the EC50 with a dashed line, and print EC50, Hill slope, and R² in a small box.
Prompt
Based on the uploaded enzyme_inhibitors.xlsx file, fit a separate 4PL curve for three inhibitors in µM, use one colorblind-safe color per compound, and sort the legend by potency with IC50 values.
Prompt
Based on the uploaded cytotoxicity_plate.csv file, fit a 4PL inhibition curve, show the 0 nM vehicle control as a separate point left of an axis break, and constrain the bottom plateau to 0.
Prompt
Based on the uploaded cell_line_resistance.csv file, fit 4PL viability curves for the parental and drug-resistant sublines of the same cell line from 0.001 to 10 µM. Draw both curves in one panel on a log10 axis, use filled circles for parental and open squares for resistant, show mean ± SEM from four replicates, add a dashed IC50 drop line for each line, and print the resistance fold shift between the two IC50 values in the upper right.
Prompt
Based on the uploaded xenograft_dosing.xlsx file, fit a four-parameter logistic curve to tumor growth inhibition measured at oral doses of 1, 3, 10, 30, and 100 mg/kg in mice. Plot dose on a log10 mg/kg axis and inhibition from 0 to 100 percent, show mean ± SEM for eight animals per dose, constrain the bottom plateau to 0, mark the ED50 with a dashed drop line, and note the group size under the x-axis label.
Add CSV, TSV, TXT, or Excel data in long format: one row per well with concentration, response, and an optional compound column. Replicate rows are welcome.
Confirm the concentration, response, and compound columns, then describe colors, error bars, IC50 or EC50 labels, and any plateau constraints.
SciFigure fits every curve, draws the figure with the computed parameters, and lets you download a PNG for papers and slides.
It fits a four-parameter logistic (4PL) model to your concentration and response measurements and draws the fitted sigmoid on a log-scaled concentration axis. Each compound or series gets its own fit, so you can compare potency across drugs, ligands, or inhibitors in one figure. Bottom and top plateaus, EC50 or IC50, Hill slope, and R² are calculated from your uploaded values before any drawing happens, which means the curve and the numbers in the legend reflect your data rather than an image model guess.
Use a long table with one row per well or replicate: a numeric concentration column, a numeric response column, and an optional compound column. Concentrations can be linear (for example nM) or already log10-transformed if the column name contains "log".
The tool calculates it. A 4PL model is fitted to your uploaded values with a least-squares optimizer, and the fitted parameters, curve coordinates, and R² are passed to the image model, which only handles layout and styling. Always check the reported values against your own analysis software before publishing.
Yes. The curve direction decides the label: decreasing responses give IC50 and increasing responses give EC50. Mention "IC50" or "EC50" in your instructions to override the automatic choice.
Every replicate row is used in the fit, and the figure shows mean ± SD at each concentration. Rows with a concentration of 0 are treated as vehicle controls, drawn separately beside an axis break, and excluded from the fit.
If the optimizer does not converge or the data show no sigmoidal trend, the figure shows the observed points without a fitted curve and the prompt states that no IC50 or EC50 could be estimated.
Yes, but verify the concentration units, normalization, fitted parameters, and replicate counts first, and describe the 4PL model and any plateau constraints in your methods section.
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