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A new online discussion forum offers a meeting spot for the gene-editing and stem cell research community to interact with one another and with the scientists that created the Allen Institute's fluorescently tagged human induced pluripotent stem cell (hiPSC) line collection.   Researchers at the Allen Institute for Cell Science were interviewed around the question "what don't we know about cells?" A full article summarizing their responses is available at alleninstitute.org.
Machine Learning Technique to Predict Human Cells' Organization Published in Nature Methods9/17/2018
Scientists at the Allen Institute have used machine learning to train computers to see parts of the cell the human eye cannot easily distinguish. Using 3D images of fluorescently labeled cells, the research team taught computers to find structures inside living cells without fluorescent labels, using only black and white images generated by an inexpensive technique known as brightfield microscopy. A study describing the new technique is published today in the journal Nature Methods.
 Our new Jove Video Journal article presents a protocol we developed for tagging endogenously expressed proteins with fluorescent tags in human induced pluripotent stem cells using CRISPR/Cas9. Putatively edited cells are enriched by fluorescence activated cell sorting and clonal cell lines are generated.
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Allen Institute for Cell Science is a part of the Allen Institute. The mission of the Allen Institute is to understand the principles that govern life, and to advance health. Our creative and multi-dimensional teams focus on answering some of the biggest questions in bioscience. We accelerate foundational research, catalyze bold ideas, develop tools and models, and openly share our science to make a broad, transformational impact on the world.
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