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FUNseq download for Windows

Free download FUNseq Windows app to run online win Wine in Ubuntu online, Fedora online or Debian online

This is the Windows app named FUNseq whose latest release can be downloaded as ProcessStack2D.exe. It can be run online in the free hosting provider OnWorks for workstations.

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- 6. Download the application and install it.

- 7. Download Wine from your Linux distributions software repositories. Once installed, you can then double-click the app to run them with Wine. You can also try PlayOnLinux, a fancy interface over Wine that will help you install popular Windows programs and games.

Wine is a way to run Windows software on Linux, but with no Windows required. Wine is an open-source Windows compatibility layer that can run Windows programs directly on any Linux desktop. Essentially, Wine is trying to re-implement enough of Windows from scratch so that it can run all those Windows applications without actually needing Windows.

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FUNseq


DESCRIPTION

This page shows the cell segmentation/tracking program for FUNseq pipeline.

Identifying a sparse subset of cancer cells from a large heterogeneous population, based on aggressive phenotypes (like invasive migration, multipolar divisions, or asymmetric lineage development) is challenging. Also, such aberration identification is critical, as cells exhibiting these characteristics are linearly correlated with poor prognosis. A high-throughput screening microscope has been developed in our group to capture these sparse, abnormal cancer cells. A program to identify these cells of interest in an accurate and fast fashion is essential. For this, we developed the mTGMM program, which tracks cells of high-throughput images, and determines the aggresive phenotypes.



Features

  • Image pre-processing: We provide methods for adjusting quality for images with heterogeous fluorescence intensity profile between cells
  • Parallel nuclei segmentation: We used agglomerative watershed for cell segmentation
  • Tracking using Gaussian models: The intensity profile of a nucleus is modelled as a 2D Gaussian distribution. Nuclei tracking is done by forwarding every Gaussian from time point t to (t + 1) using Bayesian inference, with a priori knowledge that the position, shape, overall intensity of nuclei cannot change dramatically between two consecutive time points.
  • Feature extraction: This is the post-analysis which we generate a feature table with records of cellular migration, division and intra-cellular intensity.
  • Data visualization: We provide options to visualize the cell masks, migration trajectories, cell divisions and morphology detections.



This is an application that can also be fetched from https://sourceforge.net/projects/funseq/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.


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