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16 results found

Evaluation of Deep Learning Strategies for Nucleus Segmentation in Fluorescence Images

Publication: Journal Article

Caicedo, Juan, Jonathan Roth, Allen Goodman, Tim Becker, Kyle Karhohs, Matthieu Broisin, Csaba Molnar, et al. 2019. “Evaluation of Deep Learning Strategies for Nucleus Segmentation in Fluorescence Images”. Cytometry Part A 95 (9): 952-65.

Baker-Polito Administration and Massachusetts Life Sciences Center announce $6.7 million in grant awards to data-driven life sciences capital projects

News: September 09, 2019

Massachusetts Governor Charlie Baker announced today during remarks at MassBio’s Digital Health Impact Forum in Boston that the Baker-Polito Administration and the Massachusetts Life Sciences Center (MLSC) awarded $6.7 million in capital funding to nine data-driven, cross-sector projects focused on...

JUMP-Cell Painting Consortium

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Coming soon!

Data-analysis strategies for image-based cell profiling

Publication: Journal Article

Caicedo, Juan, Sam Cooper, Florian Heigwer, Scott Warchal, Peng Qiu, Csaba Molnar, Aliaksei Vasilevich, et al. 2017. “Data-Analysis Strategies for Image-Based Cell Profiling”. Nature Methods 14 (9): 849-63.

Cell Painting

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The Carpenter lab and Schreiber lab at the Broad Institute of MIT and Harvard developed Cell Painting, a microscopy assay that generates images that reflect cell response to treatments such as drug or genetic perturbations, in high-throughput (at a scale of 100,000+ perturbations). The Carpenter lab...

Kevin Eliceiri named Fellow of the Optical Society of America

News: October 01, 2020

COBA's own Dr. Kevin Eliceiri has been named a 2021 Fellow of the Optical Society of America for outstanding research in cellular microenvironment imaging and bio-image informatics. According to the OSA: This distinction was awarded to 118 OSA members, from 24 countries, for their significant...

Weakly Supervised Learning of Single-Cell Feature Embeddings

Publication: Journal Article

Caicedo, Juan, Claire McQuin, Allen Goodman, Shantanu Singh, and Anne Carpenter. 2018. “Weakly Supervised Learning of Single-Cell Feature Embeddings”. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 9309-18.

Results

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Data is released publicly! Find the data and details at our JUMP Cell Painting Datasets landing page on Github. If you'd like to take a look at the data interactively, Ardigen provides the free, public JUMP-CP Data Explorer to search for similarities between various phenotypes and the corresponding...

More info

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Frequently Asked Questions (FAQ) Is it too late to join? When will the data be publicly available? Is it too late to join? The Consortium has finished its work optimizing, producing data, and publicly releasing it. Join our email list (below) to hear news on options to join the next phase of the...

Broad Institute launches academic-industry cell imaging consortium to speed drug discovery and development

News: July 10, 2020

The Broad Institute of MIT and Harvard today announced that the Imaging Platform, together with industry and non-profit partners, has launched a new collaboration to create a massive cell-imaging dataset, displaying more than 1 billion cells responding to over 140,000 small molecules and genetic...