NanoJ

NanoJ provides computational tools for processing and analyzing super-resolution microscopy (SRM) data, enabling spatio-temporal alignment, Super-Resolution Radial Fluctuations (SRRF) reconstruction, image quality assessment, structural modelling, and sample-environment control for nanoscale biological imaging.

Key Features:

• NanoJ-Core: High-performance computing engine that performs spatio-temporal alignment of raw super-resolution microscopy data.
• NanoJ-SRRF (Super-Resolution Radial Fluctuations): Implements SRRF to reconstruct super-resolved images from recorded SRM data.
• NanoJ-SQUIRREL: Conducts image quality assessment of super-resolved images by evaluating resolution and signal-to-noise ratio.
• NanoJ-VirusMapper: Produces structural modelling from SRM data to generate detailed models of biological structures and viral architectures.
• NanoJ-Fluidics: Controls and manages sample environmental conditions during imaging experiments.
• ImageJ integration: Operates as an extension of ImageJ to integrate with its image-analysis environment.

Scientific Applications:

• Nanoscale cellular imaging: Enables visualization and quantitative analysis of cellular components at nanoscale resolution using SRM data.
• Protein interaction analysis: Supports measurement and visualization of protein distributions and interactions from super-resolved images.
• Viral structural analysis: Facilitates modelling and analysis of viral architectures derived from SRM data.
• Quantitative super-resolution data analysis: Extracts quantitative information, including resolution and signal-to-noise metrics, from large SRM datasets.
• Fluorescent microscopy quality assessment: Assesses reliability and quality of fluorescent microscopy studies through image-quality evaluation.

Methodology:

Computational methods explicitly include spatio-temporal alignment of raw SRM data by NanoJ-Core, image reconstruction via Super-Resolution Radial Fluctuations (SRRF) in NanoJ-SRRF, image-quality assessment measuring resolution and signal-to-noise ratio in NanoJ-SQUIRREL, and structural modelling from SRM data in NanoJ-VirusMapper.