Optimizing the Cell Painting assay for image-based profiling
In image-based profiling, software extracts thousands of morphological features of cells from
multi-channel fluorescence microscopy images, yielding single-cell profiles that can be used …
multi-channel fluorescence microscopy images, yielding single-cell profiles that can be used …
Spatial omics technologies at multimodal and single cell/subcellular level
Spatial omics technologies enable a deeper understanding of cellular organizations and
interactions within a tissue of interest. These assays can identify specific compartments or …
interactions within a tissue of interest. These assays can identify specific compartments or …
Meningeal γδ T cells regulate anxiety-like behavior via IL-17a signaling in neurons
Abstract Interleukin (IL)-17a has been highly conserved during evolution of the vertebrate
immune system and widely studied in contexts of infection and autoimmunity. Studies …
immune system and widely studied in contexts of infection and autoimmunity. Studies …
Integrative in situ map** of single-cell transcriptional states and tissue histopathology in a mouse model of Alzheimer's disease
Complex diseases are characterized by spatiotemporal cellular and molecular changes that
may be difficult to comprehensively capture. However, understanding the spatiotemporal …
may be difficult to comprehensively capture. However, understanding the spatiotemporal …
Cell and nucleus shape as an indicator of tissue fluidity in carcinoma
Tissue, cell, and nucleus morphology change during tumor progression. In 2D confluent cell
cultures, different tissue states, such as fluid (unjammed) and solid (jammed), are correlated …
cultures, different tissue states, such as fluid (unjammed) and solid (jammed), are correlated …
The minimal preprocessing pipelines for the Human Connectome Project
Abstract The Human Connectome Project (HCP) faces the challenging task of bringing
multiple magnetic resonance imaging (MRI) modalities together in a common automated …
multiple magnetic resonance imaging (MRI) modalities together in a common automated …
Hierarchical feature representation and multimodal fusion with deep learning for AD/MCI diagnosis
For the last decade, it has been shown that neuroimaging can be a potential tool for the
diagnosis of Alzheimer's Disease (AD) and its prodromal stage, Mild Cognitive Impairment …
diagnosis of Alzheimer's Disease (AD) and its prodromal stage, Mild Cognitive Impairment …
Training strategies for radiology deep learning models in data-limited scenarios
Data-driven approaches have great potential to shape future practices in radiology. The
most straightforward strategy to obtain clinically accurate models is to use large, well …
most straightforward strategy to obtain clinically accurate models is to use large, well …
[KÖNYV][B] Deep learning for the Earth Sciences: A comprehensive approach to remote sensing, climate science and geosciences
DEEP LEARNING FOR THE EARTH SCIENCES Explore this insightful treatment of deep
learning in the field of earth sciences, from four leading voices Deep learning is a …
learning in the field of earth sciences, from four leading voices Deep learning is a …
Cell segmentation methods for label-free contrast microscopy: review and comprehensive comparison
Background Because of its non-destructive nature, label-free imaging is an important
strategy for studying biological processes. However, routine microscopic techniques like …
strategy for studying biological processes. However, routine microscopic techniques like …