AIMC Topic: Cells, Cultured
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A machine learning pipeline revealing heterogeneous responses to drug perturbations on vascular smooth muscle cell spheroid morphology and formation.
Scientific reports
Dec 2, 2021
Machine learning approaches have shown great promise in biology and medicine discovering hidden information to further understand complex biological and pathological processes. In this study, we developed a deep learning-based machine learning algori...
A deep learning approach to identify and segment alpha-smooth muscle actin stress fiber positive cells.
Scientific reports
Nov 8, 2021
Cardiac fibrosis is a pathological process characterized by excessive tissue deposition, matrix remodeling, and tissue stiffening, which eventually leads to organ failure. On a cellular level, the development of fibrosis is associated with the activa...
Manipulating cellular microRNAs and analyzing high-dimensional gene expression data using machine learning workflows.
STAR protocols
Oct 23, 2021
MicroRNAs (miRNAs) are elements of the gene regulatory network and manipulating their abundance is essential toward elucidating their role in patho-physiological conditions. We present a detailed workflow that identifies important miRNAs using a mach...
Risk assessment of latent tuberculosis infection through a multiplexed cytokine biosensor assay and machine learning feature selection.
Scientific reports
Oct 15, 2021
Accurate detection and risk stratification of latent tuberculosis infection (LTBI) remains a major clinical and public health problem. We hypothesize that multiparameter strategies that probe immune responses to Mycobacterium tuberculosis can provide...
Comparative mapping of crawling-cell morphodynamics in deep learning-based feature space.
PLoS computational biology
Aug 12, 2021
Navigation of fast migrating cells such as amoeba Dictyostelium and immune cells are tightly associated with their morphologies that range from steady polarized forms that support high directionality to those more complex and variable when making fre...
Robust Phase Unwrapping via Deep Image Prior for Quantitative Phase Imaging.
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Aug 10, 2021
Quantitative phase imaging (QPI) is an emerging label-free technique that produces images containing morphological and dynamical information without contrast agents. Unfortunately, the phase is wrapped in most imaging system. Phase unwrapping is the ...
An active learning approach for clustering single-cell RNA-seq data.
Laboratory investigation; a journal of technical methods and pathology
Jul 9, 2021
Single-cell RNA sequencing (scRNA-seq) data has been widely used to profile cellular heterogeneities with a high-resolution picture. Clustering analysis is a crucial step of scRNA-seq data analysis because it provides a chance to identify and uncover...
Effects of galectin-1 on immunomodulatory properties of human monocyte-derived dendritic cells.
Growth factors (Chur, Switzerland)
Jul 5, 2021
Our study aimed to evaluate the effects of Gal-1 in dose depending manner on maturation and immunomodulatory properties of monocyte-derived (Mo) DCs . The effects were analyzed by monitoring their phenotypic characteristics, cytokine profile, and the...
Deep learning-based predictive identification of neural stem cell differentiation.
Nature communications
May 10, 2021
The differentiation of neural stem cells (NSCs) into neurons is proposed to be critical in devising potential cell-based therapeutic strategies for central nervous system (CNS) diseases, however, the determination and prediction of differentiation is...
Deep Learning-Enabled Label-Free On-Chip Detection and Selective Extraction of Cell Aggregate-Laden Hydrogel Microcapsules.
Small (Weinheim an der Bergstrasse, Germany)
Apr 25, 2021
Microfluidic encapsulation of cells/tissues in hydrogel microcapsules has attracted tremendous attention in the burgeoning field of cell-based medicine. However, when encapsulating rare cells and tissues (e.g., pancreatic islets and ovarian follicles...
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