AIMC Topic: Pluripotent Stem Cells
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Label-Free Detection of Biochemical Changes during Cortical Organoid Maturation via Raman Spectroscopy and Machine Learning.
Analytical chemistry
Feb 24, 2025
Human cerebral organoids have become valuable tools in neurodevelopment research, holding promise for investigating neurological diseases and reducing drug development costs. However, clinical translation and large-scale production of brain organoids...
A spatiotemporal and machine-learning platform facilitates the manufacturing of hPSC-derived esophageal mucosa.
Developmental cell
Jan 10, 2025
Human pluripotent stem cell-derived tissue engineering offers great promise for designer cell-based personalized therapeutics, but harnessing such potential requires a deeper understanding of tissue-level interactions. We previously developed a cell ...
A deep learning approach to predict differentiation outcomes in hypothalamic-pituitary organoids.
Communications biology
Dec 6, 2024
We use three-dimensional culture systems of human pluripotent stem cells for differentiation into pituitary organoids. Three-dimensional culture is inherently characterized by its ability to induce heterogeneous cell populations, making it difficult ...
Deep learning-based models for preimplantation mouse and human embryos based on single-cell RNA sequencing.
Nature methods
Nov 14, 2024
The rapid growth of single-cell transcriptomic technology has produced an increasing number of datasets for both embryonic development and in vitro pluripotent stem cell-derived models. This avalanche of data surrounding pluripotency and the process ...
Deep Learning Powered Identification of Differentiated Early Mesoderm Cells from Pluripotent Stem Cells.
Cells
Mar 18, 2024
Pluripotent stem cells can be differentiated into all three germ-layers including ecto-, endo-, and mesoderm in vitro. However, the early identification and rapid characterization of each germ-layer in response to chemical and physical induction of d...
Deep-learning-based multi-class segmentation for automated, non-invasive routine assessment of human pluripotent stem cell culture status.
Computers in biology and medicine
Dec 11, 2020
Human induced pluripotent stem cells (hiPSCs) are capable of differentiating into a variety of human tissue cells. They offer new opportunities for personalized medicine and drug screening. This requires large quantities of high quality hiPSCs, obtai...
Viral pandemic preparedness: A pluripotent stem cell-based machine-learning platform for simulating SARS-CoV-2 infection to enable drug discovery and repurposing.
Stem cells translational medicine
Sep 22, 2020
Infection with the SARS-CoV-2 virus has rapidly become a global pandemic for which we were not prepared. Several clinical trials using previously approved drugs and drug combinations are urgently under way to improve the current situation. A vaccine ...
Machine learning uncovers cell identity regulator by histone code.
Nature communications
Jun 1, 2020
Conversion between cell types, e.g., by induced expression of master transcription factors, holds great promise for cellular therapy. Our ability to manipulate cell identity is constrained by incomplete information on cell identity genes (CIGs) and t...
Regenerative Medicine
Gene Expression Regulation
Cells
Pluripotent Stem Cells
Histone Code
Chromatin Immunoprecipitation Sequencing
Transcription Factors
Databases, Genetic
Human Umbilical Vein Endothelial Cells
RNA-Seq
Machine Learning
Gene Regulatory Networks
Epigenesis, Genetic
Algorithms
Phenotype
Humans
Deep Learning Neural Networks Highly Predict Very Early Onset of Pluripotent Stem Cell Differentiation.
Stem cell reports
Mar 14, 2019
Deep learning is a significant step forward for developing autonomous tasks. One of its branches, computer vision, allows image recognition with high accuracy thanks to the use of convolutional neural networks (CNNs). Our goal was to train a CNN with...
Machine Learning of Human Pluripotent Stem Cell-Derived Engineered Cardiac Tissue Contractility for Automated Drug Classification.
Stem cell reports
Oct 12, 2017
Accurately predicting cardioactive effects of new molecular entities for therapeutics remains a daunting challenge. Immense research effort has been focused toward creating new screening platforms that utilize human pluripotent stem cell (hPSC)-deriv...
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