Stochastic Neighbor Embedding (SNE) is a family of algorithms that create a low-dimensional representation of high-dimensional data by randomly initializing positions for each data point in low-dimensional space, and then optimizing their positions iteratively to better approximate the relationships between those data points and a sampling of their neighbors in the original high dimensional space. The defining characteristic of SNE algorithms is that the appropriate place for each data point in the low dimensional space is represented as a probability distribution for each of its neighbors.
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Dec 03, 2019 | scRNA-Seq , Flow Cytometry
SeqGeq v1.6 is the latest in bioinformatics platforms available from the team at BD Life Sciences. This update contains new features which support the analysis of bulk sequencing datasets.
Sep 25, 2019 | scRNA-Seq
Vaccines provide immunity by stimulating a set of naive B cells to become antibody-producing plasma cells against a specific pathogen. However, plasma cells have varying lifespans, which is why some vaccines, such as measles and HPV, require boosters, because once all the pathogen-specific plasma cells die, immunity ends. What drives this variation? How can we prolong a plasma cell’s life? Can longer-living plasma cells help create enduring vaccines? Could shortening a plasma cell’s lifespan prevent damage to an autoimmune patient? A team of researchers, led by Wing Lam of Washington University, sought to answer these questions about plasma cell longevity in their recent study.
May 22, 2019 | scRNA-Seq , Flow Cytometry
