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Autonomous discovery in the chemical sciences part I: Progress
This two‐part Review examines how automation has contributed to different aspects of
discovery in the chemical sciences. In this first part, we describe a classification for …
discovery in the chemical sciences. In this first part, we describe a classification for …
Robust nucleus/cell detection and segmentation in digital pathology and microscopy images: a comprehensive review
Digital pathology and microscopy image analysis is widely used for comprehensive studies
of cell morphology or tissue structure. Manual assessment is labor intensive and prone to …
of cell morphology or tissue structure. Manual assessment is labor intensive and prone to …
TLR7/8-agonist-loaded nanoparticles promote the polarization of tumour-associated macrophages to enhance cancer immunotherapy
Tumour-associated macrophages are abundant in many cancers, and often display an
immune-suppressive M2-like phenotype that fosters tumour growth and promotes resistance …
immune-suppressive M2-like phenotype that fosters tumour growth and promotes resistance …
[PDF][PDF] Data-analysis strategies for image-based cell profiling
Image-based cell profiling is a high-throughput strategy for the quantification of phenotypic
differences among a variety of cell populations. It paves the way to studying biological …
differences among a variety of cell populations. It paves the way to studying biological …
A human-machine adversarial scoring framework for urban perception assessment using street-view images
Though global-coverage urban perception datasets have been recently created using
machine learning, their efficacy in accurately assessing local urban perceptions for other …
machine learning, their efficacy in accurately assessing local urban perceptions for other …
Self-supervised deep learning encodes high-resolution features of protein subcellular localization
Explaining the diversity and complexity of protein localization is essential to fully understand
cellular architecture. Here we present cytoself, a deep-learning approach for fully self …
cellular architecture. Here we present cytoself, a deep-learning approach for fully self …
A versatile active learning workflow for optimization of genetic and metabolic networks
Optimization of biological networks is often limited by wet lab labor and cost, and the lack of
convenient computational tools. Here, we describe METIS, a versatile active machine …
convenient computational tools. Here, we describe METIS, a versatile active machine …
Bioengineering human myocardium on native extracellular matrix
Rationale: More than 25 million individuals have heart failure worldwide, with≈ 4000
patients currently awaiting heart transplantation in the United States. Donor organ shortage …
patients currently awaiting heart transplantation in the United States. Donor organ shortage …
Reconstructing cell cycle and disease progression using deep learning
We show that deep convolutional neural networks combined with nonlinear dimension
reduction enable reconstructing biological processes based on raw image data. We …
reduction enable reconstructing biological processes based on raw image data. We …
Improved structure, function and compatibility for CellProfiler: modular high-throughput image analysis software
There is a strong and growing need in the biology research community for accurate,
automated image analysis. Here, we describe CellProfiler 2.0, which has been engineered …
automated image analysis. Here, we describe CellProfiler 2.0, which has been engineered …