AIMC Topic: Cell Differentiation
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AI-guided laser purification of human iPSC-derived cardiomyocytes for next-generation cardiac cell manufacturing.
Communications biology
May 13, 2025
Current methods for producing cardiomyocytes from human induced pluripotent stem cells (hiPSCs) using 2D monolayer differentiation are often hampered by batch-to-batch variability and inefficient purification processes. Here, we introduce CM-AI, a no...
What insights can spatiotemporal esophageal atlases and deep learning bring to engineering the esophageal mucosa?
Developmental cell
May 5, 2025
In this issue of Developmental Cell, Yang et al. present an integrated experimental and computational platform that maps the spatiotemporal development of the human esophagus and predicts key signaling pathways governing epithelial differentiation. T...
FateNet: an integration of dynamical systems and deep learning for cell fate prediction.
Bioinformatics (Oxford, England)
Sep 2, 2024
MOTIVATION: Understanding cellular decision-making, particularly its timing and impact on the biological system such as tissue health and function, is a fundamental challenge in biology and medicine. Existing methods for inferring fate decisions and ...
Deep Learning Method for Estimating Germ-layer Regions of Early Differentiated Human Induced Pluripotent Stem Cells on Micropattern Using Bright-field Microscopy Image.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Live cell staining is expensive and may bring potential safety issues in downstream clinical applications, bright-field images rather than staining images should be more suitable to reveal time-series changes of differentiating hiPSCs (human induced ...
Artificial Intelligence Supports Automated Characterization of Differentiated Human Pluripotent Stem Cells.
Stem cells (Dayton, Ohio)
Sep 15, 2023
Revolutionary advances in AI and deep learning in recent years have resulted in an upsurge of papers exploring applications within the biomedical field. Within stem cell research, promising results have been reported from analyses of microscopy image...
OPUS-Rota4: a gradient-based protein side-chain modeling framework assisted by deep learning-based predictors.
Briefings in bioinformatics
Jan 17, 2022
Accurate protein side-chain modeling is crucial for protein folding and protein design. In the past decades, many successful methods have been proposed to address this issue. However, most of them depend on the discrete samples from the rotamer libra...
Detection and Weak Segmentation of Masses in Gray-Scale Breast Mammogram Images Using Deep Learning.
Yonsei medical journal
Jan 1, 2022
PURPOSE: In this paper, we propose deep-learning methodology with which to enhance the mass differentiation performance of convolutional neural network (CNN)-based architecture.
[Naringenin promotes osteogenic differentiation of BMSCs via SDF-1α/CXCR4 signaling axis].
Shanghai kou qiang yi xue = Shanghai journal of stomatology
Dec 1, 2021
PURPOSE: To explore the influence of naringenin on osteogenic differentiation of bone mesenchymal stem cells(BMSCs), and the role of SDF-1α/CXCR4 signaling axis in the osteogenic differentiation by naringenin.
Application of a deep learning-based image analysis and live-cell imaging system for quantifying adipogenic differentiation kinetics of adipose-derived stem/stromal cells.
Adipocyte
Dec 1, 2021
Quantitative methods for assessing differentiative potency of adipose-derived stem/stromal cells may lead to improved clinical application of this multipotent stem cell, by advancing our understanding of specific processes such as adipogenic differen...
Highly accurate differentiation of bone marrow cell morphologies using deep neural networks on a large image data set.
Blood
Nov 18, 2021
Biomedical applications of deep learning algorithms rely on large expert annotated data sets. The classification of bone marrow (BM) cell cytomorphology, an important cornerstone of hematological diagnosis, is still done manually thousands of times e...
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