An open house showcasing Seattle-area cell biology research
Event highlights include:
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.
The Allen Cell Collection now contains five new fluorescently tagged stem cell lines, including the first cells in the collection with a tag specific to heart muscle cells, or cardiomyocytes. To date, all the cell lines have been gene edited to carry a fluorescent marker that is produced in undifferentiated cells, before they go on to become specific cell types, like cardiomyocytes, nerve cells or liver cells.
 To ensure researchers have success working with our human induced pluripotent stem cell lines in their lab, our Angel Nelson highlights nuanced techniques and helpful tips while demonstrating our cardiac differentiation protocol for the WTC parental line and our gene-edited cells. If the experiment is successful, you can expect to see beating cardiomyocytes at day 7.
The Allen Institute for Cell Science today launched the Allen Integrated Cell, the world's first predictive and comprehensive 3D model of a live human cell. This new visualization of a large collection of human stem cells will allow researchers around the world to see structures inside a living cell together at the same time, providing a baseline for better understanding healthy cells and for studying human disease models. Building off last year's launch of the Allen Cell Explorer, the Allen Integrated Cell comprises two different models that can predict the shape and location of cellular structures. The first, a probabilistic model, emerged from a machine learning approach that accurately predicts the most probable shape and location of structures in a cell based solely on the shape of that cell's plasma membrane and nucleus. 
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