AI Medical Compendium Journal:
Cell reports

Showing 1 to 10 of 23 articles

Temporally discordant chromatin accessibility and DNA demethylation define short- and long-term enhancer regulation during cell fate specification.

Cell reports
Chromatin and DNA modifications mediate the transcriptional activity of lineage-specifying enhancers, but recent work challenges the dogma that joint chromatin accessibility and DNA demethylation are prerequisites for transcription. To understand thi...

Machine learning uncovers the transcriptional regulatory network for the production host Streptomyces albidoflavus.

Cell reports
Streptomyces albidoflavus is a widely used strain for natural product discovery and production through heterologous biosynthetic gene clusters (BGCs). However, the transcriptional regulatory network (TRN) and its impact on secondary metabolism remain...

Machine learning reveals prominent spontaneous behavioral changes and treatment efficacy in humanized and transgenic Alzheimer's disease models.

Cell reports
Computer-vision and machine-learning (ML) approaches are being developed to provide scalable, unbiased, and sensitive methods to assess mouse behavior. Here, we used the ML-based variational animal motion embedding (VAME) segmentation platform to ass...

Controlling human causal inference through in silico task design.

Cell reports
Learning causal relationships is crucial for survival. The human brain's functional flexibility allows for effective causal inference, underlying various learning processes. While past studies focused on environmental factors influencing causal infer...

A robot-rodent interaction arena with adjustable spatial complexity for ethologically relevant behavioral studies.

Cell reports
Outside of the laboratory, animals behave in spaces where they can transition between open areas and coverage as they interact with others. Replicating these conditions in the laboratory can be difficult to control and record. This has led to a domin...

Comparison of visual quantities in untrained neural networks.

Cell reports
The ability to compare quantities of visual objects with two distinct measures, proportion and difference, is observed even in newborn animals. However, how this function originates in the brain, even before visual experience, remains unknown. Here, ...

Machine-Learning-Based Analysis in Genome-Edited Cells Reveals the Efficiency of Clathrin-Mediated Endocytosis.

Cell reports
Cells internalize various molecules through clathrin-mediated endocytosis (CME). Previous live-cell imaging studies suggested that CME is inefficient, with about half of the events terminated. These CME efficiency estimates may have been confounded b...

Semi-supervised Learning Predicts Approximately One Third of the Alternative Splicing Isoforms as Functional Proteins.

Cell reports
Alternative splicing acts on transcripts from almost all human multi-exon genes. Notwithstanding its ubiquity, fundamental ramifications of splicing on protein expression remain unresolved. The number and identity of spliced transcripts that form sta...

Interpretable deep learning translation of GWAS and multi-omics findings to identify pathobiology and drug repurposing in Alzheimer's disease.

Cell reports
Translating human genetic findings (genome-wide association studies [GWAS]) to pathobiology and therapeutic discovery remains a major challenge for Alzheimer's disease (AD). We present a network topology-based deep learning framework to identify dise...

Fear memory-associated synaptic and mitochondrial changes revealed by deep learning-based processing of electron microscopy data.

Cell reports
Serial section electron microscopy (ssEM) can provide comprehensive 3D ultrastructural information of the brain with exceptional computational cost. Targeted reconstruction of subcellular structures from ssEM datasets is less computationally demandin...