FT-ITC Analysis

Across experiments

See the patterns beyond one titration.

FT-ITC Analysis brings related experiments together for global fitting, temperature evaluation and advanced thermodynamic interpretation.

The analysis result

One place to review the result across your experiments.

Move from individual fits to a result that makes the relationship between experiments legible. Review shared and experiment-specific parameters, fit quality and residuals without losing the underlying datasets.

01

Average parameters

Summarise fitted values across replicates and selected experiments.

02

Temperature evaluation

Examine temperature-dependent behaviour and derived relationships such as ΔCp.

03

Traceable context

Keep the contributing experiments, assumptions and model choices close to the result.

Global analysis

Fit related experiments as a connected question.

Optimise multiple isotherms simultaneously, decide which parameters are shared, and keep other parameters experiment-specific where that is scientifically appropriate.

01

Combine active datasets

Analyse experiments collected across temperatures, buffers, salt conditions or replicates as one connected result.

02

Set meaningful relationships

Share selected parameters or connect them through physical relationships while retaining experiment-level values where needed.

03

Review the evidence

Read global parameters together with individual isotherms, residuals and the experiments contributing to the fit.

Advanced analyses

What changes when binding happens?

When an experiment series is designed for it, FT-ITC Analysis supports additional views of the physical processes behind binding.

02

Salt dependence

Evaluate ionic-strength effects and estimate the selected model's extrapolated dissociation constant at zero ionic strength.

03

Proton linkage

Compare titrations across buffers with different protonation enthalpies to investigate linked protonation changes.

Further reading

Advanced interpretation starts with the literature.

Read the underlying methods and review the assumptions before drawing specialised conclusions.