From f7e044632cd8a45e258f825cc10933574486cf61 Mon Sep 17 00:00:00 2001 From: ejfertig Date: Sat, 10 Nov 2018 17:09:44 -0500 Subject: [PATCH] intro edits --- content/04.body.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/content/04.body.md b/content/04.body.md index 6d61b7d..128a146 100644 --- a/content/04.body.md +++ b/content/04.body.md @@ -8,10 +8,10 @@ that preserve the important attributes of the original high dimensional data and interpretable, searchable features. For transcriptomic data, compressing on the gene dimension is most attractive: it can be applied to single samples, and genes often provide information about other co-regulated genes or cellular attributes. We hypothesize that building an ensemble of low dimensional representations across latent space methods will provide a -reduced dimensional space that captures biological sources of variability that is robust to measurement noise. Our seed network will +reduced dimensional space that captures biological sources of variability and is robust to measurement noise. Our seed network will incorporate biologists and computer scientists from five leading academic institutions who will work together to create foundational technologies and educational opportunities that promote effective interpretation of low dimensional representations of HCA data. We will continue our active collaborations with other -members of the broader HCA network to integrate state of the art latent space tools, portals, and annotations to enable biological utilization of the resulting low dimensional catalogue of HCA data. +members of the broader HCA network to integrate state of the art latent space tools, portals, and annotations to enable biological utilization of HCA data through latent spaces. ## Scientific Goals