AIMC Topic: Cell Lineage
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Integrative transcriptomic analysis reveals oligodendrocyte lineage switching in multiple sclerosis.
Life science alliance
Aug 4, 2025
Multiple sclerosis (MS) is a chronic disease of the central nervous system. The occurrence of MS is a phased process while its cause is still unclear. Here, by combining white matter single-nucleus transcriptomic datasets from MS and control samples,...
Interpretable machine learning-guided single-cell mapping deciphers multi-lineage pancreatic dysregulation in type 2 diabetes.
Cardiovascular diabetology
Jul 24, 2025
BACKGROUND: Pancreatic cellular heterogeneity is fundamental to systemic metabolic regulation, yet its pathological remodeling in diabetes remains poorly characterized.
A library of lineage-specific driver lines connects developing neuronal circuits to behavior in the ventral nerve cord.
eLife
Jun 10, 2025
Understanding developmental changes in neuronal lineages is crucial to elucidate how they assemble into functional neural networks. Studies investigating nervous system development in model systems have only focused on select regions of the CNS due t...
X-scPAE: An explainable deep learning model for embryonic lineage allocation prediction based on single-cell transcriptomics revealing key genes in embryonic cell development.
Computers in biology and medicine
Feb 12, 2025
In single-cell transcriptomics research, accurately predicting cell lineage allocation and identifying differences between lineages are crucial for understanding cell differentiation processes and reducing early pregnancy miscarriages in humans. This...
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 ...
Visualizing and Comparing Machine Learning Predictions to Improve Human-AI Teaming on the Example of Cell Lineage.
IEEE transactions on visualization and computer graphics
Feb 28, 2024
We visualize the predictions of multiple machine learning models to help biologists as they interactively make decisions about cell lineage-the development of a (plant) embryo from a single ovum cell. Based on a confocal microscopy dataset, tradition...
Single-cell segmentation in bacterial biofilms with an optimized deep learning method enables tracking of cell lineages and measurements of growth rates.
Molecular microbiology
Apr 17, 2023
Bacteria often grow into matrix-encased three-dimensional (3D) biofilm communities, which can be imaged at cellular resolution using confocal microscopy. From these 3D images, measurements of single-cell properties with high spatiotemporal resolution...
Artificial Intelligence in Bone Marrow Histological Diagnostics: Potential Applications and Challenges.
Pathobiology : journal of immunopathology, molecular and cellular biology
Feb 15, 2023
The expanding digitalization of routine diagnostic histological slides holds a potential to apply artificial intelligence (AI) to pathology, including bone marrow (BM) histology. In this perspective, we describe potential tasks in diagnostics that ca...
Tracking cell lineages in 3D by incremental deep learning.
eLife
Jan 6, 2022
Deep learning is emerging as a powerful approach for bioimage analysis. Its use in cell tracking is limited by the scarcity of annotated data for the training of deep-learning models. Moreover, annotation, training, prediction, and proofreading curre...
Robotic high-throughput biomanufacturing and functional differentiation of human pluripotent stem cells.
Stem cell reports
Dec 2, 2021
Efficient translation of human induced pluripotent stem cells (hiPSCs) requires scalable cell manufacturing strategies for optimal self-renewal and functional differentiation. Traditional manual cell culture is variable and labor intensive, posing ch...
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