This program is designed to fit and simulate experimental nuclear magnetic resonance (NMR) rotating frame relaxation-dispersion (R1rho) data by solving the Bloch-McConnell partial differential equations describing chemical exchange in an external magnetic field using eigenvalue decomposition.
- Can fit 1D R1rho data using the Bloch-McConnell equations or with the Laguerre algegraic approximations.
- Can fit directly to decaying intensities instead of R1rho (plotting functionality limited).
- Currently supports 2- and 3-state fitting.
- Reports fit statistics metrics such as reduced chi-square, adjusted R-square, TSS, etc.
- Fits for excited state (ES) populations, exchange rates, ES free-energies and transition state barriers, and intrinsic rate constants (R1/R2)
- Error in fitted parameters can be estimated using standard-error or by Monte-Carlo resampling if given error in R1rho values.
- Can fit multiple datasets together using combinations of shared parameters.
- e.g. Datasets A and B fitted sharing pB and kexAB
- Plots R1rho and R2eff fits as well as residuals.
- BM fits can be fit assuming ground-state or average-state alignment, or 'auto' which will fit using the best alignment given by the exchange regime.
- Supports grid-search over N-dimensional parameter space in log or linear spaced increments and plotting the search results.
- Supports model comparison using Akaike's Information Criterion (AIC) and Bayesian Information Criterion (AIC).
- Simulate decaying intensities, R1rho, R2eff, and 3D projections of decaying GS/ES vectors.
- Noise corrupt intensities or R1rho.
It is recommended that you use an Anaconda environment to run BMNS. The conda_bmns.sh bash script will install the required Python dependencies.
bash conda_bmns.sh bmns
source activate bmnsExamples for how to fit and simulate R1rho data can be found within the Examples folder.
python BMNS.py -fit Examples/Fit-Indv-2State/Fit-InputPars.txt Examples/Fit-Indv-2State/ Output_2state/- Finish writing function docstrings
- Port to Python 3