On September 5, 2021, SuperResNET v3.6 is released online. Version 3.6 has the following added features:
The cluster/blob area feature (for projected 2D blob) is added to the list of features. In total, we have 30 extracted features now.
The user can now interactively select/deselect the feature(s) she/he wants to use for grouping the blobs. For example, the user can select the shape features (i.e., FA, CL, CP, CS) only to group the blobs or any other group of features.
Added a check box for the features normalization. The user can decide if she/he wants to normalize the features or not before applying k-means to group the blobs.
The number of groups (k) in k-means can be selected to be up to 200 groups.
Fixed the issue of having different k-means results if one ran multiple times for the same k and same data. This issue is fixed by sorting the group centers and then, re-label the blobs in a consistent way.
Fixed the group coloring by including more colors for large k (i.e., k = 200).
Fixed some visualization issues from the previous version.
SuperResNET is compiled under the new MATLAB 2021a release to get the benefits of the new MATLAB improvements
On February 20, 2021, SuperResNET v3.5 is released online. Version 3.5 has the following added features:
Added four new methods for manual ROI interactive selection.
Added more features when loading the data.
Visualized the data directly after loading.
The features and meta-information are displayed after calculations.
Fixed some issues in the blob's feature extraction. The 2D/3D blob features are supported for the 3D blobs.
Autoload the data after selecting the data file.
Support many of the data formats for various SMLM microscopes
Added tooltips and self explanatory panels for the tabs.
Added Ripley's H-function.
Added cancel button for Ripley’s H-function that allows the user to cancel the calculation at any time (i.e., when having a very large number of localizations).
Added more control to Ripley's function. The user can select r_min, r_max, and the step size for the range of scales to be calculated for the H-function.
Fixed some of the visualization issues.
Fixed some of the software bugs from the previous version.
Introduce a new tab for the modularity analysis and visualization of the blobs.
Introduce a new tab for the blobs retrieval.
Added DBSCAN as another method to segment the blobs. DBSCAN is added to support segmenting non-blob like structures.
Added t-SNE visualization for the embedded features of the blobs.
Created this website to keep track of SuperResNET new features.
In February 2021, SuperResNET become public and online for the first time
The users can download and install their own copy of SuperResNET.
SuperResNET gets its name after the previous SuperNet name.
SuperResNET is compiled to support Mac and Windows OS users.
SuperResNET pre v3.5
For internal testing and not released publicly
First release in October 2019 implementing the methods presented in the following papers:
 Khater IM, Meng F, Wong TH, Nabi IR, Hamarneh G. Super resolution network analysis defines the molecular architecture of caveolae and caveolin-1 scaffolds. Scientific reports. 2018 Jun 13;8(1):9009.
 Khater IM, Liu Q, Chou KC, Hamarneh G, Nabi IR. Super-resolution modularity analysis shows polyhedral caveolin-1 oligomers combine to form scaffolds and caveolae. Scientific reports. 2019 Jul 8;9(1):1-0.