High-content screening for quantitative cell biology
High-content screening (HCS), which combines automated fluorescence microscopy with
quantitative image analysis, allows the acquisition of unbiased multiparametric data at the …
quantitative image analysis, allows the acquisition of unbiased multiparametric data at the …
Machine learning in cell biology–teaching computers to recognize phenotypes
Recent advances in microscope automation provide new opportunities for high-throughput
cell biology, such as image-based screening. High-complex image analysis tasks often …
cell biology, such as image-based screening. High-complex image analysis tasks often …
Handcrafted vs. non-handcrafted features for computer vision classification
This work presents a generic computer vision system designed for exploiting trained deep
Convolutional Neural Networks (CNN) as a generic feature extractor and mixing these …
Convolutional Neural Networks (CNN) as a generic feature extractor and mixing these …
An artificial intelligence-based stacked ensemble approach for prediction of protein subcellular localization in confocal microscopy images
Predicting subcellular protein localization has become a popular topic due to its utility in
understanding disease mechanisms and develo** innovative drugs. With the rapid …
understanding disease mechanisms and develo** innovative drugs. With the rapid …
Deep CNNs for microscopic image classification by exploiting transfer learning and feature concatenation
Deep convolutional neural networks (CNNs) have become one of the state-of-the-art
methods for image classification in various domains. For biomedical image classification …
methods for image classification in various domains. For biomedical image classification …
DNA damage during S-phase mediates the proliferation-quiescence decision in the subsequent G1 via p21 expression
Following DNA damage caused by exogenous sources, such as ionizing radiation, the
tumour suppressor p53 mediates cell cycle arrest via expression of the CDK inhibitor, p21 …
tumour suppressor p53 mediates cell cycle arrest via expression of the CDK inhibitor, p21 …
Cellular heterogeneity: do differences make a difference?
SJ Altschuler, LF Wu - Cell, 2010 - cell.com
A central challenge of biology is to understand how individual cells process information and
respond to perturbations. Much of our knowledge is based on ensemble measurements …
respond to perturbations. Much of our knowledge is based on ensemble measurements …
CellProfiler: image analysis software for identifying and quantifying cell phenotypes
Biologists can now prepare and image thousands of samples per day using automation,
enabling chemical screens and functional genomics (for example, using RNA interference) …
enabling chemical screens and functional genomics (for example, using RNA interference) …
Deep learning is combined with massive-scale citizen science to improve large-scale image classification
Pattern recognition and classification of images are key challenges throughout the life
sciences. We combined two approaches for large-scale classification of fluorescence …
sciences. We combined two approaches for large-scale classification of fluorescence …
High performing ensemble of convolutional neural networks for insect pest image detection
Pest infestation is a major cause of crop damage and lost revenues worldwide. Automatic
identification of invasive insects would significantly speed up the recognition of pests and …
identification of invasive insects would significantly speed up the recognition of pests and …