Related Articles

Motivation

Graphical user interface (GUI) software promotes novelty by allowing users to extend the functionality. SVM Classifier is a cross-platform graphical application that handles very large datasets well. The purpose of this study is to create a GUI application that allows SVM users to perform SVM training, classification and prediction.

Results

The GUI provides user-friendly access to state-of-the-art SVM methods embodied in the LIBSVM implementation of Support Vector Machine. We implemented the java interface using standard swing libraries.

We used a sample data from a breast cancer study for testing classification accuracy. We achieved 100% accuracy in classification among the BRCA1–BRCA2 samples with RBF kernel of SVM.

Conclusion

We have developed a java GUI application that allows SVM users to perform SVM training, classification and prediction. We have demonstrated that support vector machines can accurately classify genes into functional categories based upon expression data from DNA microarray hybridization experiments. Among the different kernel functions that we examined, the SVM that uses a radial basis kernel function provides the best performance.

The SVM Classifier is available at .

The lateral mobility of individual, incoming human papillomavirus type 16 pseudoviruses (PsV) bound to live HeLa cells was studied by single particle tracking using fluorescence video microscopy. The trajectories were computationally analyzed in terms of diffusion rate and mode of motion as described by the moment scaling spectrum. Four distinct modes of mobility were seen: confined movement in small zones (30–60 nm in diameter), confined movement with a slow drift, fast random motion with transient confinement, and linear, directed movement for long distances. The directed movement was most prominent on actin-rich cell protrusions such as filopodia or retraction fibres, where the rate was similar to that measured for actin retrograde flow. It was, moreover, sensitive to perturbants of actin retrograde flow such as cytochalasin D, jasplakinolide, and blebbistatin. We found that transport along actin protrusions significantly enhanced HPV-16 infection in sparse tissue culture, cells suggesting a role for in vivo infection of basal keratinocytes during wound healing.

Author Summary

To replicate, viruses have to enter into host cells. Since they have no means of locomotion, they rely entirely on cellular transport systems to access the cellular compartments where replication occurs. Following individual virus particles by video microscopy, we found that human papillomavirus type 16, the main causative agent of cervical cancer, bound to long finger-like protrusions of cells. There, they were transported from the periphery to the cell body. The transport was mediated by a process termed actin retrograde flow, where viruses bound to cell surface molecules hooked up to filamentuos actin and were dragged along with the actin-like items on a transport belt. Entry into the cell occured at the cell body. The results raised the interesting possibility that viruses use retrograde flow when they infect wounded epidermal keratinocytes, where finger-like protrusions of cells are abundant.

Background

Gastrointestinal contractions are controlled by an underlying bioelectrical activity. High-resolution spatiotemporal electrical mapping has become an important advance for investigating gastrointestinal electrical behaviors in health and motility disorders. However, research progress has been constrained by the low efficiency of the data analysis tasks. This work introduces a new efficient software package: GEMS (Gastrointestinal Electrical Mapping Suite), for analyzing and visualizing high-resolution multi-electrode gastrointestinal mapping data in spatiotemporal detail.

Results

GEMS incorporates a number of new and previously validated automated analytical and visualization methods into a coherent framework coupled to an intuitive and user-friendly graphical user interface. GEMS is implemented using MATLAB®, which combines sophisticated mathematical operations and GUI compatibility. Recorded slow wave data can be filtered via a range of inbuilt techniques, efficiently analyzed via automated event-detection and cycle clustering algorithms, and high quality isochronal activation maps, velocity field maps, amplitude maps, frequency (time interval) maps and data animations can be rapidly generated. Normal and dysrhythmic activities can be analyzed, including initiation and conduction abnormalities. The software is distributed free to academics via a community user website and forum (http://sites.google.com/site/gimappingsuite).

Conclusions

This software allows for the rapid analysis and generation of critical results from gastrointestinal high-resolution electrical mapping data, including quantitative analysis and graphical outputs for qualitative analysis. The software is designed to be used by non-experts in data and signal processing, and is intended to be used by clinical researchers as well as physiologists and bioengineers. The use and distribution of this software package will greatly accelerate efforts to improve the understanding of the causes and clinical consequences of gastrointestinal electrical disorders, through high-resolution electrical mapping.

Graphic User Interface (GUI) is commonly considered to be superior to Text-based User Interface (TUI). This study compares GUI and TUI in an electronic dental record system. Several usability analysis techniques compared the relative effectiveness of a GUI and a TUI. Expert users and novice users were evaluated in time required and steps needed to complete the task. A within-subject design was used to evaluate if the experience with either interface will affect task performance. The results show that the GUI interface was not better than the TUI for expert users. GUI interface was better for novice users. For novice users there was a learning transfer effect from TUI to GUI. This means a user interface is user-friendly or not depending on the mapping between the user interface and tasks. GUI by itself may or may not be better than TUI.

Time-lapsed films of particle motion on the leading lamella of chick heart fibroblasts and mouse peritoneal macrophages were analyzed. The particles were composed of powdered glass or powdered aminated polystyrene and were 0.5-1.0 micrometer in radius. Particle motions were described by steps in position from one frame to the time-lapse movies to the next. The statistics of the step-size distribution of the particles were consistent with a particle in Brownian motion subject to a constant force. From the Brownian movement, we have calculated the two-dimensional diffusion coefficient of different particles. These vary by more than an order of magnitude (10(-11)-10(-10) cm2/s) even for particles composed of the same material and located very close to each other on the surface of the cell. This variation was not correlated with particle size but is interpretable as a result of different numbers of adhesive bonds holding the particles to the cells. The constant component of particle movement can be interpreted as a result of a constant force acting on each particle (0.1-1.0 x 10(-8) dyn). Variations in the fractional coefficient for particles close to each other on the cell surface do not yield corresponding differences in velocity, suggesting that the frictional coefficient and the driving force vary together. This is consistent with the hypothesis that the particles are carried by flow of the membrane as a whole or by flow of some submembrane material. The utility of our methods for monitoring cell motile behavior in biologically interesting situations, such as a chemotactic gradient, is discussed.

We present an Anti-Brownian Electrokinetic trap (ABEL trap) capable of trapping individual fluorescently labeled protein molecules in aqueous buffer. The ABEL trap operates by tracking the Brownian motion of a single fluorescent particle in solution, and applying a time-dependent electric field designed to induce an electrokinetic drift that cancels the Brownian motion. The trapping strength of the ABEL trap is limited by the latency of the feedback loop. In previous versions of the trap, this latency was set by the finite frame rate of the camera used for video-tracking. In the present system, the motion of the particle is tracked entirely in hardware (without a camera or image-processing software) using a rapidly rotating laser focus and lock-in detection. The feedback latency is set by the finite rate of arrival of photons. We demonstrate trapping of individual molecules of the protein GroEL in buffer, and we show confinement of single fluorophores of the dye Cy3 in water.

This Technical Note describes a novel modular framework for development and interlaboratory distribution and validation of 3D tractography algorithms based on in vivo diffusion tensor imaging (DTI) measurements. The proposed framework allows individual MRI research centers to benefit from new tractography algorithms developed at other independent centers by “plugging” new tractography modules directly into their own custom DTI software tools, such as existing graphical user interfaces (GUI) for visualizing brain white matter pathways. The proposed framework is based on the Java 3D programming platform, which provides an object-oriented programming (OOP) model and independence of computer hardware configuration and operating system. To demonstrate the utility of the proposed approach, a complete GUI for interactive DTI tractography was developed, along with two separate and interchangeable modules that implement two different tractography algorithms. Although the application discussed here relates to DTI tractography, the programming concepts presented here should be of interest to anyone who wishes to develop platform-independent GUI applications for interactive 3D visualization.

Background

Good statistical models for analyzing and simulating multilocus recombination data exist but are not accessible to many biologists because their use requires reasonably sophisticated mathematical and computational implementation. While some labs have direct access to statisticians or programmers competent to carry out such analyses, many labs do not. We have created a platform independent application with an easy-to-use graphical user interface that will carry out such analyses including the simulations needed to bootstrap confidence intervals for the parameters of interest. This software should make multi-locus techniques accessible to labs that previously relied on less powerful and potentially statistically confounded single interval or double interval techniques.

Results

We introduce InterferenceAnalyzer, an implementation with a user-friendly graphical interface incorporating previously developed algorithms for the analysis and simulation of multilocus recombination data. We demonstrate the use and features of the program with an example of multilocus tetrad data from the mustard plant, Arabidopsis thaliana, and the yeast, Saccharomyces cerevisiae.

Conclusion

InterferenceAnalyzer provides easy access to the powerful and appropriate statistical tools for the multi-locus analysis of genetic data.

Neurofilaments are long flexible cytoplasmic protein polymers that are transported rapidly but intermittently along the axonal processes of nerve cells. Current methods for studying this movement involve manual tracking of fluorescently tagged neurofilament polymers in videos acquired by time-lapse fluorescence microscopy. Here, we describe an automated tracking method that uses particle filtering to implement a recursive Bayesian estimation of the filament location in successive frames of video sequences. To increase the efficiency of this approach, we take advantage of the fact that neurofilament movement is confined within the boundaries of the axon. We use piecewise cubic spline interpolation to model the path of the axon and then we use this model to limit both the orientation and location of the neurofilament in the particle tracking algorithm. Based on these two spatial constraints, we develop a prior dynamic state model that generates significantly fewer particles than generic particle filtering, and we select an adequate observation model to produce a robust tracking method. We demonstrate the efficacy and efficiency of our method by performing tracking experiments on real time-lapse image sequences of neurofilament movement, and we show that the method performs well compared to manual tracking by an experienced user. This spatially constrained particle filtering approach should also be applicable to the movement of other axonally transported cargoes.

Brownian dynamics (BD) in a suitably constructed potential of mean force is an efficient and accurate method for simulating ion transport through wide ion channels. Here, a web-based graphical user interface (GUI) is presented for grand canonical Monte Carlo (GCMC) BD simulations of channel proteins: http://www.charmm-gui.org/input/gcmcbd. The webserver is designed to help users avoid most of the technical difficulties and issues encountered in setting up and simulating complex pore systems. GCMC/BD simulation results for three proteins, the voltage dependent anion channel (VDAC), α-Hemolysin, and the protective antigen pore of the anthrax toxin (PA), are presented to illustrate system setup, input preparation, and typical output (conductance, ion density profile, ion selectivity, and ion asymmetry). Two models for the input diffusion constants for potassium and chloride ions in the pore are compared: scaling of the bulk diffusion constants by 0.5, as deduced from previous all-atom molecular dynamics simulations of VDAC; and a hydrodynamics based model (HD) of diffusion through a tube. The HD model yields excellent agreement with experimental conductances for VDAC and α-Hemolysin, while scaling bulk diffusion constants by 0.5 leads to underestimates of 10–20%. For PA, simulated ion conduction values overestimate experimental values by a factor of 1.5 to 7 (depending on His protonation state and the transmembrane potential), implying that the currently available computational model of this protein requires further structural refinement.

Construction of a cone-beam computed tomography (CBCT) system for laboratory research usually requires integration of different software and hardware components. As a result, building and operating such a complex system require the expertise of researchers with significantly different backgrounds. Additionally, writing flexible code to control the hardware components of a CBCT system combined with designing a friendly graphical user interface (GUI) can be cumbersome and time consuming. An intuitive and flexible program structure, as well as the program GUI for CBCT acquisition, is presented in this note. The program was developed in National Instrument’s Laboratory Virtual Instrumentation Engineering Workbench (LabVIEW) graphical language and is designed to control a custom-built CBCT system but has been also used in a standard angiographic suite. The hardware components are commercially available to researchers and are in general provided with software drivers which are Lab-VIEW compatible. The program structure was designed as a sequential chain. Each step in the chain takes care of one or two hardware commands at a time; the execution of the sequence can be modified according to the CBCT system design. We have scanned and reconstructed over 200 specimens using this interface and present three examples which cover different areas of interest encountered in laboratory research. The resulting 3D data are rendered using a commercial workstation. The program described in this paper is available for use or improvement by other researchers.

Construction of a cone-beam computed tomography (CBCT) system for laboratory research usually requires integration of different software and hardware components. As a result, building and operating such a complex system require the expertise of researchers with significantly different backgrounds. Additionally, writing flexible code to control the hardware components of a CBCT system combined with designing a friendly graphical user interface (GUI) can be cumbersome and time consuming. An intuitive and flexible program structure, as well as the program GUI for CBCT acquisition, is presented in this note. The program was developed in National Instrument’s Laboratory Virtual Instrumentation Engineering Workbench (LabVIEW) graphical language and is designed to control a custom-built CBCT system but has been also used in a standard angiographic suite. The hardware components are commercially available to researchers and are in general provided with software drivers which are LabVIEW compatible. The program structure was designed as a sequential chain. Each step in the chain takes care of one or two hardware commands at a time; the execution of the sequence can be modified according to the CBCT system design. We have scanned and reconstructed over 200 specimens using this interface and present three examples which cover different areas of interest encountered in laboratory research. The resulting 3D data are rendered using a commercial workstation. The program described in this paper is available for use or improvement by other researchers.

How viruses are transmitted across the mucosal epithelia of the respiratory, digestive, or excretory tracts, and how they spread from cell to cell and cause systemic infections, is incompletely understood. Recent advances from single virus tracking experiments have revealed conserved patterns of virus movements on the plasma membrane, including diffusive motions, drifting motions depending on retrograde flow of actin filaments or actin tail formation by polymerization, and confinement to submicrometer areas. Here, we discuss how viruses take advantage of cellular mechanisms that normally drive the movements of proteins and lipids on the cell surface. A concept emerges where short periods of fast diffusive motions allow viruses to rapidly move over several micrometers. Coupling to actin flow supports directional transport of virus particles during entry and cell-cell transmission, and local confinement coincides with either nonproductive stalling or infectious endocytic uptake. These conserved features of virus–host interactions upstream of infectious entry offer new perspectives for anti-viral interference.

Background

Wavelets have proven to be a powerful technique for the analysis of periodic data, such as those that arise in the analysis of circadian oscillators. While many implementations of both continuous and discrete wavelet transforms are available, we are aware of no software that has been designed with the nontechnical end-user in mind. By developing a toolkit that makes these analyses accessible to end users without significant programming experience, we hope to promote the more widespread use of wavelet analysis.

Findings

We have developed the WAVOS toolkit for wavelet analysis and visualization of oscillatory systems. WAVOS features both the continuous (Morlet) and discrete (Daubechies) wavelet transforms, with a simple, user-friendly graphical user interface within MATLAB. The interface allows for data to be imported from a number of standard file formats, visualized, processed and analyzed, and exported without use of the command line. Our work has been motivated by the challenges of circadian data, thus default settings appropriate to the analysis of such data have been pre-selected in order to minimize the need for fine-tuning. The toolkit is flexible enough to deal with a wide range of oscillatory signals, however, and may be used in more general contexts.

Conclusions

We have presented WAVOS: a comprehensive wavelet-based MATLAB toolkit that allows for easy visualization, exploration, and analysis of oscillatory data. WAVOS includes both the Morlet continuous wavelet transform and the Daubechies discrete wavelet transform. We have illustrated the use of WAVOS, and demonstrated its utility for the analysis of circadian data on both bioluminesence and wheel-running data. WAVOS is freely available at http://sourceforge.net/projects/wavos/files/

We have developed a Matlab/C toolbox, Brain-SMART (System for Multivariate AutoRegressive Time series, or BSMART), for spectral analysis of continuous neural time series data recorded simultaneously from multiple sensors. Available functions include time series data importing/exporting, preprocessing (normalization and trend removal), AutoRegressive (AR) modeling (multivariate/bivariate model estimation and validation), spectral quantity estimation (auto power, coherence and Granger causality spectra), network analysis (including coherence and causality networks) and visualization (including data, power, coherence and causality views). The tools for investigating causal network structures are unique functions provided by this toolbox. All functionality has been integrated into a simple and user-friendly graphical user interface (GUI) environment designed for easy accessibility. Although we have tested the toolbox only on Windows and Linux operating systems, BSMART itself is system independent. This toolbox is freely available (http://www.sahs.uth.tmc.edu/hliang/software.htm) under the GNU public license for open source development.

Background

The application of computational modeling to rationally design drugs and characterize macro biomolecular receptors has proven increasingly useful due to the accessibility of computing clusters and clouds. AutoDock is a well-known and powerful software program used to model ligand to receptor binding interactions. In its current version, AutoDock requires significant amounts of user time to setup and run jobs, and collect results. This paper presents DockoMatic, a user friendly Graphical User Interface (GUI) application that eases and automates the creation and management of AutoDock jobs for high throughput screening of ligand to receptor interactions.

Results

DockoMatic allows the user to invoke and manage AutoDock jobs on a single computer or cluster, including jobs for evaluating secondary ligand interactions. It also automates the process of collecting, summarizing, and viewing results. In addition, DockoMatic automates creation of peptide ligand .pdb files from strings of single-letter amino acid abbreviations.

Conclusions

DockoMatic significantly reduces the complexity of managing multiple AutoDock jobs by facilitating ligand and AutoDock job creation and management.

The biological effects of acute particulate air pollution exposure in host innate immunity remain obscure and have relied largely on in vitro models. We hypothesized that single acute exposure to ambient or engineered particulate matter (PM) in the absence of other secondary stimuli would activate lung dendritic cells (DC) in vivo and provide information on the early immunological events of PM exposure and DC activation in a mouse model naïve to prior PM exposure. Activation of purified lung DC was studied following oropharyngeal instillation of ambient particulate matter (APM). We compared the effects of APM exposure with that of diesel-enriched PM (DEP), carbon black particles (CBP) and silver nanoparticles (AgP). We found that PM species induced variable cellular infiltration in the lungs and only APM exposure induced eosinophilic infiltration. Both APM and DEP activated pulmonary DC and promoted a Th2-type cytokine response from naïve CD4+ T cells ex vivo. Cultures of primary peribronchial lymph node cells from mice exposed to APM and DEP also displayed a Th2-type immune response ex vivo. We conclude that exposure of the lower airway to various PM species induces differential immunological responses and immunomodulation of DC subsets. Environmental APM and DEP activated DC in vivo and provoked a Th2 response ex vivo. By contrast, CBP and AgP induced altered lung tissue barrier integrity but failed to stimulate CD4+ T cells as effectively. Our work suggests that respirable pollutants activate the innate immune response with enhanced DC activation, pulmonary inflammation and Th2-immune responsiveness.

In this paper we present a high-fidelity method for 2D and 3D image boundary segmentation. The algorithm is a novel combination of graph-cuts and initial image segmentation. The pre-segmentation using anisotropic vector diffusion and the fast marching method is employed so that the size of the graph being considered is significantly reduced. To further improve the segmentation accuracy, some user guidance is taken into account in finding the minimal graph cut. To this end, a user-friendly graphical user interface (GUI) is developed not only for visualization purposes but for user input and editing as well. The approaches and tools developed are validated on a number of 2D/3D biomedical imaging data, showing the high efficiency and effectiveness of our method.

Movements of transferrin and alpha 2-macroglobulin receptor molecules in the plasma membrane of cultured normal rat kidney (NRK) fibroblastic cells were investigated by video-enhanced contrast optical microscopy with 1.8 nm spatial precision and 33 ms temporal resolution by labeling the receptors with the ligand-coated nanometer-sized colloidal gold particles. For both receptor species, most of the movement trajectories are of the confined diffusion type, within domains of approximately 0.25 microns2 (500-700 nm in diagonal length). Movement within the domains is random with a diffusion coefficient approximately 10(-9) cm2/s, which is consistent with that expected for free Brownian diffusion of proteins in the plasma membrane. The receptor molecules move from one domain to one of the adjacent domains at an average frequency of 0.034 s-1 (the residence time within a domain approximately 29 s), indicating that the plasma membrane is compartmentalized for diffusion of membrane receptors and that long- range diffusion is the result of successive intercompartmental jumps. The macroscopic diffusion coefficients for these two receptor molecules calculated on the basis of the compartment size and the intercompartmental jump rate are approximately 2.4 x 10(-11) cm2/s, which is consistent with those determined by averaging the long-term movements of many particles. Partial destruction of the cytoskeleton decreased the confined diffusion mode, increased the simple diffusion mode, and induced the directed diffusion (transport) mode. These results suggest that the boundaries between compartments are made of dynamically fluctuating membrane skeletons (membrane-skeleton fence model).

Background

Researchers wishing to conduct genetic association analysis involving single nucleotide polymorphisms (SNPs) or haplotypes are often confronted with the lack of user-friendly graphical analysis tools, requiring sophisticated statistical and informatics expertise to perform relatively straightforward tasks. Tools, such as the SimHap package for the R statistics language, provide the necessary statistical operations to conduct sophisticated genetic analysis, but lacks a graphical user interface that allows anyone but a professional statistician to effectively utilise the tool.

Results

We have developed SimHap GUI, a cross-platform integrated graphical analysis tool for conducting epidemiological, single SNP and haplotype-based association analysis. SimHap GUI features a novel workflow interface that guides the user through each logical step of the analysis process, making it accessible to both novice and advanced users. This tool provides a seamless interface to the SimHap R package, while providing enhanced functionality such as sophisticated data checking, automated data conversion, and real-time estimations of haplotype simulation progress.

Conclusion

SimHap GUI provides a novel, easy-to-use, cross-platform solution for conducting a range of genetic and non-genetic association analyses. This provides a free alternative to commercial statistics packages that is specifically designed for genetic association analysis.

Automatic estimation of current dipoles from biomagnetic data is still a problematic task. This is due not only to the ill-posedness of the inverse problem but also to two intrinsic difficulties introduced by the dipolar model: the unknown number of sources and the nonlinear relationship between the source locations and the data. Recently, we have developed a new Bayesian approach, particle filtering, based on dynamical tracking of the dipole constellation. Contrary to many dipole-based methods, particle filtering does not assume stationarity of the source configuration: the number of dipoles and their positions are estimated and updated dynamically during the course of the MEG sequence. We have now developed a Matlab-based graphical user interface, which allows nonexpert users to do automatic dipole estimation from MEG data with particle filtering. In the present paper, we describe the main features of the software and show the analysis of both a synthetic data set and an experimental dataset.

Background

Modern omics research involves the application of high-throughput technologies that generate vast volumes of data. These data need to be pre-processed, analyzed and integrated with existing knowledge through the use of diverse sets of software tools, models and databases. The analyses are often interdependent and chained together to form complex workflows or pipelines. Given the volume of the data used and the multitude of computational resources available, specialized pipeline software is required to make high-throughput analysis of large-scale omics datasets feasible.

Results

We have developed a generic pipeline system called Cyrille2. The system is modular in design and consists of three functionally distinct parts: 1) a web based, graphical user interface (GUI) that enables a pipeline operator to manage the system; 2) the Scheduler, which forms the functional core of the system and which tracks what data enters the system and determines what jobs must be scheduled for execution, and; 3) the Executor, which searches for scheduled jobs and executes these on a compute cluster.

Conclusion

The Cyrille2 system is an extensible, modular system, implementing the stated requirements. Cyrille2 enables easy creation and execution of high throughput, flexible bioinformatics pipelines.

Microtubule-dependent transport of vesicles and organelles appears saltatory because particles switch between periods of rest, random Brownian motion, and active transport. The transport can be regulated through motor proteins, cargo adaptors, or microtubule tracks. We report here a mechanism whereby microtubule associated proteins (MAPs) represent obstacles to motors which can be regulated by microtubule affinity regulating kinase (MARK)/Par-1, a family of kinases that is known for its involvement in establishing cell polarity and in phosphorylating tau protein during Alzheimer neurodegeneration. Expression of MARK causes the phosphorylation of MAPs at their KXGS motifs, thereby detaching MAPs from the microtubules and thus facilitating the transport of particles. This occurs without impairing the intrinsic activity of motors because the velocity during active movement remains unchanged. In primary retinal ganglion cells, transfection with tau leads to the inhibition of axonal transport of mitochondria, APP vesicles, and other cell components which leads to starvation of axons and vulnerability against stress. This transport inhibition can be rescued by phosphorylating tau with MARK.

Gromita is a fully integrated and efficient graphical user interface (GUI) to the recently updated molecular dynamics suite Gromacs, version 4. Gromita is a cross-platform, perl/tcl-tk based, interactive front end designed to break the command line barrier and introduce a new user-friendly environment to run molecular dynamics simulations through Gromacs. Our GUI features a novel workflow interface that guides the user through each logical step of the molecular dynamics setup process, making it accessible to both advanced and novice users. This tool provides a seamless interface to the Gromacs package, while providing enhanced functionality by speeding up and simplifying the task of setting up molecular dynamics simulations of biological systems. Gromita can be freely downloaded from http://bio.demokritos.gr/gromita/.

Reaction kinetics for complex, highly-interconnected kinetic schemes are modeled using analytical solutions to a system of ordinary differential equations. The algorithm employs standard linear algebra methods that are implemented using MatLab functions in a Visual Basic interface. A graphical user interface for simple entry of reaction schemes facilitates comparison of a variety of reaction schemes. To ensure microscopic balance, graph theory algorithms are used to determine violations of thermodynamic cycle constraints. Analytical solutions based on linear differential equations result in fast comparisons of first order kinetic rates and amplitudes as a function of changing ligand concentrations. For analysis of higher order kinetics, we also implemented a solution using numerical integration. In order to determine rate constants from experimental data, fitting algorithms using the Levenberg-Marquardt algorithm or using Broyden-Fletcher-Goldfarb-Shanno (BFGS) methods were implemented that adjust rate constants to fit the model to imported data. We have included the ability to carry out global fitting of data sets obtained at varying ligand concentrations. These tools are combined in a single package, which we have dubbed VisKin, to guide and analyze kinetic experiments. The software is available online for use on PCs.