ForSDAT: an automated platform for analyzing force spectroscopy measurements
文献情報
Tal Duanis-Assaf, Yair Razvag, Meital Reches
Single molecule force spectroscopy using an atomic force microscope is a common method in the study of ligand–receptor interactions, adhesion events and protein folding. Such experiments often produce thousands of force vs. distance curves. Manually analyzing these data is prone to bias and human error, and is extremely time consuming. Most analysis software available offer limited automation of specific interaction detection. Moreover, automatic open-source programs commonly employ force thresholding to distinguish specific interactions from non-specific interactions. This approach is sensitive to a low signal/noise ratio (SNR) and requires optimization for each set of results. This work presents ForSDAT, the Force Spectroscopy Data Analysis Toolkit, as a tool for completely automated data analysis, and describes in detail the analysis algorithm. The results show that ForSDAT analyzes the curves with a high degree of success. Furthermore, ForSDAT is highly modular and can be easily fitted to different analysis processes and extended with custom components, and can therefore be used in different research fields.
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Analytical Methods

Analytical Methods welcomes early applications of new analytical and bioanalytical methods and technology demonstrating the potential for societal impact. We require that methods and technology reported in the journal are sufficiently innovative, robust, accurate, and compared to other available methods for the intended application. Developments with interdisciplinary approaches are particularly welcome. Systems should be proven with suitably complex and analytically challenging samples. We encourage developments within, but not limited to, the following technologies and applications: global health, point-of-care and molecular diagnostics biosensors and bioengineering drug development and pharmaceutical analysis applied microfluidics and nanotechnology omics studies, such as proteomics, metabolomics or glycomics environmental, agricultural and food science neuroscience biochemical and clinical analysis forensic analysis industrial process and method development














