AI Medical Compendium Journal:
Molecular biology of the cell

Showing 1 to 10 of 10 articles

Deep learning-driven imaging of cell division and cell growth across an entire eukaryotic life cycle.

Molecular biology of the cell
The life cycle of eukaryotic microorganisms involves complex transitions between states such as dormancy, mating, meiosis, and cell division, which are often studied independently from each other. Therefore, most microbial life cycles are theoretical...

Deep learning-based image classification reveals heterogeneous execution of cell death fates during viral infection.

Molecular biology of the cell
Cell fate decisions, such as proliferation, differentiation, and death, are driven by complex molecular interactions and signaling cascades. While significant progress has been made in understanding the molecular determinants of these processes, hist...

Precise measurement of nanoscopic septin ring structures with deep learning-assisted quantitative superresolution microscopy.

Molecular biology of the cell
The combination of image analysis and superresolution microscopy methods allows for unprecedented insight into the organization of macromolecular assemblies in cells. Advances in deep learning (DL)-based object recognition enable the automated proces...

Receptor tyrosine kinase MET ligand-interaction classified via machine learning from single-particle tracking data.

Molecular biology of the cell
Internalin B-mediated activation of the membrane-bound receptor tyrosine kinase MET is accompanied by a change in receptor mobility. Conversely, it should be possible to infer from receptor mobility whether a cell has been treated with internalin B. ...

DynaMorph: self-supervised learning of morphodynamic states of live cells.

Molecular biology of the cell
A cell's shape and motion represent fundamental aspects of cell identity and can be highly predictive of function and pathology. However, automated analysis of the morphodynamic states remains challenging for most cell types, especially primary human...

Robust classification of cell cycle phase and biological feature extraction by image-based deep learning.

Molecular biology of the cell
Across the cell cycle, the subcellular organization undergoes major spatiotemporal changes that could in principle contain biological features that could potentially represent cell cycle phase. We applied convolutional neural network-based classifier...

Digging deep into Golgi phenotypic diversity with unsupervised machine learning.

Molecular biology of the cell
The synthesis of glycans and the sorting of proteins are critical functions of the Golgi apparatus and depend on its highly complex and compartmentalized architecture. High-content image analysis coupled to RNA interference screening offers opportuni...

Nano Random Forests to mine protein complexes and their relationships in quantitative proteomics data.

Molecular biology of the cell
Ever-increasing numbers of quantitative proteomics data sets constitute an underexploited resource for investigating protein function. Multiprotein complexes often follow consistent trends in these experiments, which could provide insights about thei...

AI: A transformative opportunity in cell biology.

Molecular biology of the cell
The success of artificial intelligence (AI) algorithms in predicting protein structure and more recently, protein interactions, demonstrates the power and potential of machine learning and AI for advancing and accelerating biomedical research. As cel...

Ciliate behavior: blueprints for dynamic cell biology and microscale robotics.

Molecular biology of the cell
Place a drop of pond water under the microscope, and you will likely find an ocean of extraordinary and diverse single-celled organisms called . This remarkable group of single-celled organisms wield microtubules, active systems, electrical signaling...