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We demonstrate that a HeLa cancer cell classifier selectively identifies HeLa cells and triggers apoptosis without affecting non-HeLa cell types.
These similar values suggest that cell classifier is robust to cell size variation.
The second step applies cell classifier to recognize whether the image is positive (that is, it contains true fluorescent kinetoplasts).
Cell classifier was set on area-lower limit on bright field channel (25 for PBMCs and 50 for monocyte derived macrophages and cell lines) to avoid acquiring debris.
Other examples of specific environmental sensing devices include a powerful multi-input miRNA-based cell classifier circuit that can distinguish between different cancer cell types and the use of the E. coli nitric oxide (NO) sensing system NorR to detect this important marker for gut inflammation in inflammatory bowel disease (IBD).
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Cell classifiers are genetic logic circuits that transduce endogenous molecular inputs into cell-type-specific responses.
An efficient computational algorithm is developed to design microRNA-based synthetic cell classifiers and to optimize their performance.
Cell classifiers were applied to the BF channel to capture objects that ranged between 50 and 300 units on an arbitrary scale.
This work deals with the design and development of HEp-2 cells classifier.
In the simplest case of multidimensional classification where each dimension can be classified independently, the problem can be trivially solved by a cell population classifier consisting of a mixture of cells capable of responding individually to just one input using the circuit described in Figure 1.
To build more sophisticated functions, logic operations such as inverters and 2-input Boolean gates have been layered together to generate feedforward circuits, half adders (and subtractors), 2-input decoders, and a cell type classifier.
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