Suggestions

[koalive]

Hi! While updating the repository, I came across the following references, for which I was unsure if they are in the scope, if they are too redundant with the content already included or I was simply unable to judge if they should be included or not. I believe most could be useful for the community but are not necessary involving image-based profiling tasks directly.

Functionally-Relevant Morphological Profiling: A Tool to Assess Cellular Heterogeneity
Morphological profiling of small molecules
Label-free cell cycle analysis for high-throughput imaging flow cytometry
Automated analysis of high-content microscopy data with deep learning
Time series modeling of live-cell shape dynamics for image-based phenotypic profiling
Domain-invariant features for mechanism of action prediction in a multi-cell-line drug screen
Classifying and segmenting microscopy images with deep multiple instance learning
KCML: a machine‐learning framework for inference of multi‐scale gene functions from genetic perturbation screens
Visualizing quantitative microscopy data: History and challenges
Transfer Learning with Deep Convolutional Neural Networks for Classifying Cellular Morphological Changes
High-content phenotypic and pathway profiling to advance drug discovery in diseases of unmet need
RefCell: multi-dimensional analysis of image-based high-throughput screens based on ‘typical cells’
Pooled CRISPR screens with imaging on microraft arrays reveals stress granule-regulatory factors
Label-free prediction of three-dimensional fluorescence images from transmitted-light microscopy
High-content analysis screening for cell cycle regulators using arrayed synthetic crRNA libraries
Deep learning is combined with massive-scale citizen science to improve large-scale image classification
Content-aware image restoration: pushing the limits of fluorescence microscopy
Optical Pooled Screens in Human Cells

If you think some of those articles are awesome for image-based profiling of biological phenotypes, feel free to submit a PR!