QUB Express

• interactive hidden Markov model building and simulation: simulates recordings from one molecule or an ensemble, at equilibrium or responding to a stimulus protocol
• baseline correction and event detection: Viterbi and Kalman methods can pick a single-molecule signal out of substantial noise
• maximum likelihood optimization of model parameters, for single molecule and ensemble data, with constraints
• burst detection, statistics and clustering: lists "bursts" (event clusters separated by long inactivity), plots properties such as Popen, and algorithmically splits the list into groups (K-Means)
• measurement and histograms
• nonlinear least-squares curve fitting of any figure, to any user-entered curve function
• model search: evaluates likelihood of all connection schemes

• "live" simulation responds to each change in the model, unless paused
• streamlined stimulus assignment when optimizing with data that has a stimulus signal
• the single-molecule optimizer (MIL/MSL) can handle data with a stimulus signal e.g. varying ligand concentration or voltage
• unlimited undo/redo in the model
• automatic lab notebook saved as an HTML document while you work; output can be customized, scripted, and/or redirected to other programs
• fewer clicks, fewer legacy options
• scriptable, hosts plugins: can record actions as a Python script; some panels are already plugins; 3rd-party plugins welcome
• runs on Linux, Mac OS X and Windows

• data acquisition (or use QUBIO)
• dynamic clamp: use this custom QuB
• model merge: combines two models into one, with appropriate constraints
• MIL with channel count > 1
• staircase algorithms: for unidirectional data e.g. molecular motor position
• Kalman background subtraction: tracks and removes periodic noise
• misc. options including multi-file extraction, some dose-response simulations, some figures

QuB Classic

• interactive hidden Markov model building and simulation: simulates recordings from one molecule or an ensemble, at equilibrium or responding to a stimulus protocol
• baseline correction and event detection: Markov and Kalman methods can pick a single-molecule signal out of substantial noise
• maximum likelihood optimization of model parameters, for single molecule and ensemble data, with constraints
• burst detection, statistics and clustering: lists "bursts" (event clusters separated by long inactivity), plots properties such as Popen, and algorithmically splits the list into groups (K-Means)
• measurement and histograms
• nonlinear least-squares curve fitting of any figure, to any user-entered curve function
• model search: evaluates likelihood of all connection schemes

• data acquisition (or use QUBIO)
• dynamic clamp: use this custom QuB
• model merge: combines two models into one, with appropriate constraints
• MIL with channel count > 1
• model building and optimization scripts such as star, chain, perturb, clasify, survey
• staircase algorithms: for unidirectional data e.g. molecular motor position
• Kalman background subtraction: tracks and removes periodic noise
• misc. options including multi-file extraction, some dose-response simulations, some figures

• "live" simulation responds to each change in the model, unless paused
• streamlined stimulus assignment when optimizing with data that has a stimulus signal
• the single-molecule optimizer (MIL/MSL) can handle data with a stimulus signal e.g. varying ligand concentration or voltage
• unlimited undo/redo in the model
• automatic lab notebook saved as an HTML document while you work; output can be customized, scripted, and/or redirected to other programs
• fewer clicks, fewer legacy options
• scriptable, hosts plugins: can record actions as a Python script; some panels are already plugins; 3rd-party plugins welcome
• runs on Linux, Mac OS X and Windows

QUBIO

• records and generates analog and digital signals using National Instruments M-series hardware.

Fitness

• nonlinear least-squares curve fitting
• user-defined curves can be any function(series1, series2, ...), with access to functions from numpy and scipy
• fitting curve can be a user-defined first-order ODE system
• user-defined weighting can be any column or function of columns
• strategy script helps automate difficult fits by specifying when to fit parameters and when to hold them
• resample by delta replaces flat regions of data with a single point, to emphasize dynamic features
• K-Means clustering divides datapoints into K groups, minimizing square distance from group centroid
• "X-Means" provides distance- and likelihood-based metrics to help decide which K is best
• automatic lab notebook saved as an HTML document while you work; output can be customized, scripted, and/or redirected to other programs
• scriptable, hosts plugins: can record actions as a Python script; some panels are already plugins; 3rd-party plugins welcome
• runs on Linux, Mac OS X and Windows

X-Means

• K-Means clustering divides datapoints into K groups, minimizing square distance from group centroid
• "X-Means" provides distance- and likelihood-based metrics to help decide which K is best
• clusters based on one or more columns of tabular data
• runs as a web app in modern web browsers