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Researchers use 'hole-y' math and machine learning to study cellular self-assembly


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IMAGE: Topology-based machine learning classifies how human cells organize into spatial patterns based on the presence of persistent topological loops around empty regions, which can be used to infer cellular behaviors.
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Credit: Wong lab/Brown University
PROVIDENCE, R.I. [Brown University] The field of mathematical topology is often described in terms of donuts and pretzels.
To most of us, the two differ in the way they taste or in their compatibility with morning coffee. But to a topologist, the only difference between the two is that one has a single hole and the other has three. There s no way to stretch or contort a donut to make it look like a pretzel at least not without ripping it or pasting different parts together, both of which are verboten in topology. The different number of holes make two shapes that are fundamentally, inexorably different. ....

Dhananjay Bhaskar , Iany Wong , William Zhang , Brown School Of Engineering , Brown University , Brown University Data Science Initiative , Soft Matter , Pablo Picasso , National Cancer Institute , Brown University Data Science , Cell Biology , Mathematics Statistics , Algorithms Models , Technology Engineering Computer Science , Biomedical Environmental Chemical Engineering , Robotry Artificial Intelligence , தனஞ்சய் பாஸ்கர் , வில்லியம் ஜாங் , பழுப்பு பள்ளி ஆஃப் பொறியியல் , பழுப்பு பல்கலைக்கழகம் , மென்மையான விஷயம் , பப்லொ பிகாஸொ , தேசிய புற்றுநோய் நிறுவனம் ,