carpenterlab's repositories
unet4nuclei
U-net based segmentation of nuclei in microscopy images
2019_caicedo_dsb
Analysis of results of the Data Science Bowl 2018
2016_Bray_NatureProtocols
Supporting data files, documentation, and updated tips for the Cell Painting protocol
2019_Caicedo_CytometryA
Evaluation of Deep Learning Strategies for Nucleus Segmentation in Fluorescence Images
2016_Pawlowski_MLCB
Supporting materials for automated morphological profiling using pre-trained deep convolutional networks
open-science-rules
Collaboratively written manuscript discussing Ten Simple Rules for Enabling Open Science in Biomedical Research
2018_Rohban_NatComm
Capturing single-cell heterogeneity via data fusion improves image-based profiling
2019_Doan_CytometryA
Label-free monitoring of acute lymphoblastic leukemia by computer vision
2019_carpenter_eliceiri_ibiology
Information about iBiology's freely available animation of a deep convolution neural network
2019_Doan_PNAS
Label-free assessment of red blood cell storage lesions by deep learning
2017_Goldsborough_MLCB
CytoGAN: Generative Modeling of Cell Images
2019_Lafarge_MIDL
Extended Variational Auto-Encoder for Single-Cell Representation
2021_Stirling_BMCBioInformatics
Supplemental material for Stirling et al