AIMC Topic: Cell Cycle

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High precision tracking analysis of cell position and motion fields using 3D U-net network models.

Computers in biology and medicine Jan 26, 2023
Cells are the basic units of biological organization, and the quantitative analysis of cellular states is an important topic in medicine and is valuable in revealing the complex mechanisms of microscopic world organisms. In order to better understand...
Models, Biological Cell Cycle Cell Division Neural Networks, Computer Cell Movement
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Synthetic Micrographs of Bacteria (SyMBac) allows accurate segmentation of bacterial cells using deep neural networks.

BMC biology Nov 30, 2022
BACKGROUND: Deep-learning-based image segmentation models are required for accurate processing of high-throughput timelapse imaging data of bacterial cells. However, the performance of any such model strictly depends on the quality and quantity of tr...
Machine Learning Bacteria Microscopy Humans Neural Networks, Computer Cell Cycle
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Identification of Human Cell Cycle Phase Markers Based on Single-Cell RNA-Seq Data by Using Machine Learning Methods.

BioMed research international Aug 13, 2022
The cell cycle is composed of a series of ordered, highly regulated processes through which a cell grows and duplicates its genome and eventually divides into two daughter cells. According to the complex changes in cell structure and biosynthesis, th...
Machine Learning Biomarkers RNA-Seq Humans Mitosis Cell Cycle
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Deep learning tools and modeling to estimate the temporal expression of cell cycle proteins from 2D still images.

PLoS computational biology Mar 14, 2022
Automatic characterization of fluorescent labeling in intact mammalian tissues remains a challenge due to the lack of quantifying techniques capable of segregating densely packed nuclei and intricate tissue patterns. Here, we describe a powerful deep...
Mice Mammals Cell Cycle Cell Cycle Proteins Cell Nucleus Animals Deep Learning Image Processing, Computer-Assisted
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Universal prediction of cell-cycle position using transfer learning.

Genome biology Jan 31, 2022
BACKGROUND: The cell cycle is a highly conserved, continuous process which controls faithful replication and division of cells. Single-cell technologies have enabled increasingly precise measurements of the cell cycle both as a biological process of ...
Single-Cell Analysis Sequence Analysis, RNA Principal Component Analysis Machine Learning Cell Cycle Exome Sequencing
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Mitotic Index Determination on Live Cells From Label-Free Acquired Quantitative Phase Images Using a Supervised Autoencoder.

IEEE/ACM transactions on computational biology and bioinformatics Dec 8, 2021
This interdisciplinary work focuses on the interest of a new auto-encoder for supervised classification of live cell populations growing in a thermostated imaging station and acquired by a Quantitative Phase Imaging (QPI) camera. This type of camera ...
Nocodazole Supervised Machine Learning Microscopy Cell Cycle Mitotic Index HeLa Cells Humans Algorithms Image Processing, Computer-Assisted
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Regression plane concept for analysing continuous cellular processes with machine learning.

Nature communications May 5, 2021
Biological processes are inherently continuous, and the chance of phenotypic discovery is significantly restricted by discretising them. Using multi-parametric active regression we introduce the Regression Plane (RP), a user-friendly discovery tool e...
Membrane Proteins Cell Differentiation Carcinoma, Hepatocellular Cell Cycle Cell Physiological Phenomena Drosophila melanogaster Biological Phenomena Supervised Machine Learning Machine Learning Humans Animals Cell Line, Tumor
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A convolutional neural network segments yeast microscopy images with high accuracy.

Nature communications Nov 12, 2020
The identification of cell borders ('segmentation') in microscopy images constitutes a bottleneck for large-scale experiments. For the model organism Saccharomyces cerevisiae, current segmentation methods face challenges when cells bud, crowd, or exh...
Neural Networks, Computer Software Microscopy Saccharomyces cerevisiae Image Processing, Computer-Assisted Cell Cycle
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Robust classification of cell cycle phase and biological feature extraction by image-based deep learning.

Molecular biology of the cell Apr 22, 2020
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...
Humans NIH 3T3 Cells Animals Microtubules Cell Line Deep Learning Cell Nucleus Cell Cycle Image Processing, Computer-Assisted Microscopy, Fluorescence Golgi Apparatus Mice HeLa Cells
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Quantitative assessment of cancer cell morphology and motility using telecentric digital holographic microscopy and machine learning.

Cytometry. Part A : the journal of the International Society for Analytical Cytology Dec 28, 2017
The noninvasive, fast acquisition of quantitative phase maps using digital holographic microscopy (DHM) allows tracking of rapid cellular motility on transparent substrates. On two-dimensional surfaces in vitro, MDA-MB-231 cancer cells assume several...
Cell Adhesion Holography Neoplasm Invasiveness Microscopy, Fluorescence Humans Cell Nucleus Cell Line, Tumor Actins Breast Neoplasms Machine Learning Cell Cycle Cell Movement
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