10 August 2017
To address these issues, we developed the R-based open source web browser application Frapbot, which is compatible with all available Internet browsers and thereby independent of any operating system. Frapbot comes along with an intuitive user interface and provides the functionalities for automated analyses of datasets using a novel pattern recognition algorithm that recognizes relevant columns and identifies the presence or absence of prebleach values and the time point of photobleaching. This unsupervised strategy allows an instant overview over the collected data, endorsing a conclusion over the FRAP data quality free from observer bias. Alternatively, Frapbot can be used for supervised processing and analysis of FRAP data by manual control of individual steps in the algorithm. The results are provided as .zip file, which contains .csv formatted output tables. Frapbot users can also download the source code package and perform the analysis offline in any R programming environment.
Frapbot has been successfully published at Cytometry-A and the platform is accessible via www.frapbot.com.
Robin Kohze Samuel Schmidt
Robin Kohze and Samuel Schmidt, Dept. of Biochemistry, theme Nanomedicine have released a new open source R-based web application for the analysis of Fluorescence Recovery After Photobleaching (FRAP) data.
FRAP is a commonly used technique to obtain information about the ensemble mobility of fluorescent molecules and thereby determine the kinetics of diffusion, e.g. in the cellular membrane. Currently, FRAP data processing and analyses are often performed using commercial software packages, that are not generally available to all researchers and restricted to certain operating systems. Moreover, they often provide only a limited set of functionalities, which are required for correcting, scaling, normalizing and fitting of FRAP data.To address these issues, we developed the R-based open source web browser application Frapbot, which is compatible with all available Internet browsers and thereby independent of any operating system. Frapbot comes along with an intuitive user interface and provides the functionalities for automated analyses of datasets using a novel pattern recognition algorithm that recognizes relevant columns and identifies the presence or absence of prebleach values and the time point of photobleaching. This unsupervised strategy allows an instant overview over the collected data, endorsing a conclusion over the FRAP data quality free from observer bias. Alternatively, Frapbot can be used for supervised processing and analysis of FRAP data by manual control of individual steps in the algorithm. The results are provided as .zip file, which contains .csv formatted output tables. Frapbot users can also download the source code package and perform the analysis offline in any R programming environment.
Frapbot has been successfully published at Cytometry-A and the platform is accessible via www.frapbot.com.
Robin Kohze Samuel Schmidt