AI Medical Compendium Journal:
Cell reports

Showing 11 to 20 of 23 articles

Learning to represent continuous variables in heterogeneous neural networks.

Cell reports
Animals must monitor continuous variables such as position or head direction. Manifold attractor networks-which enable a continuum of persistent neuronal states-provide a key framework to explain this monitoring ability. Neural networks with symmetri...

Universal encoding of pan-cancer histology by deep texture representations.

Cell reports
Cancer histological images contain rich biological and clinical information, but quantitative representation can be problematic and has prevented the direct comparison and accumulation of large-scale datasets. Here, we show successful universal encod...

A functional module states framework reveals transcriptional states for drug and target prediction.

Cell reports
Cells are complex systems in which many functions are performed by different genetically defined and encoded functional modules. To systematically understand how these modules respond to drug or genetic perturbations, we develop a functional module s...

Using graph convolutional neural networks to learn a representation for glycans.

Cell reports
As the only nonlinear and the most diverse biological sequence, glycans offer substantial challenges for computational biology. These carbohydrates participate in nearly all biological processes-from protein folding to viral cell entry-yet are still ...

Merged Affinity Network Association Clustering: Joint multi-omic/clinical clustering to identify disease endotypes.

Cell reports
Although clinical and laboratory data have long been used to guide medical practice, this information is rarely integrated with multi-omic data to identify endotypes. We present Merged Affinity Network Association Clustering (MANAclust), a coding-fre...

Predicting protein condensate formation using machine learning.

Cell reports
Membraneless organelles are liquid condensates, which form through liquid-liquid phase separation. Recent advances show that phase separation is essential for cellular homeostasis by regulating basic cellular processes, including transcription and si...

Deep neural networks identify signaling mechanisms of ErbB-family drug resistance from a continuous cell morphology space.

Cell reports
It is well known that the development of drug resistance in cancer cells can lead to changes in cell morphology. Here, we describe the use of deep neural networks to analyze this relationship, demonstrating that complex cell morphologies can encode s...

Machine Learning Uncovers Food- and Excipient-Drug Interactions.

Cell reports
Inactive ingredients and generally recognized as safe compounds are regarded by the US Food and Drug Administration (FDA) as benign for human consumption within specified dose ranges, but a growing body of research has revealed that many inactive ing...

Multiplexing of Information about Self and Others in Hippocampal Ensembles.

Cell reports
In addition to coding a subject's location in space, the hippocampus has been suggested to code social information, including the spatial position of conspecifics. "Social place cells" have been reported for tasks in which an observer mimics the beha...