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Neal G. Ravindra's Projects

cluster2celltype icon cluster2celltype

Using biological priors (previously selected important features or "markers"), assign cell types to clusters based on differential discriminability of cell type markers

condense icon condense

CONditional DENSity Embedding for unsupervised characterization of gene dynamics

covid_severity_index icon covid_severity_index

CSI developed in the early days, published in https://www.annemergmed.com/article/S0196-0644(20)30588-6/fulltext

cpa icon cpa

The Compositional Perturbation Autoencoder (CPA) is a deep generative framework to learn effects of perturbations at the single-cell level. CPA performs OOD predictions of unseen combinations of drugs, learns interpretable embeddings, estimates dose-response curves, and provides uncertainty estimates.

diffuse_profile icon diffuse_profile

How to diffuse a profile into a shared space for recommendations? Should we use supervised learning and feature attribution or variance metrics for perturbation profiles? How to evaluate this approach?

dlmodules icon dlmodules

3 month-ish thematic modules to keep up with new developments in other fields -- blogging, writing a textbook, implementing code from scratch

new2dev icon new2dev

Playground for new computational implementations in order to appropriately tweak and transition to personal prj dev

scgat icon scgat

Code to reproduce results in Ravindra NG* & Sehanobish A* et al. 2020, "Disease State Prediction From Single-Cell Data Using Graph Attention Networks" to appear in ACM Proceedings. <https://arxiv.org/abs/2002.07128>

scnd icon scnd

neurodegeneration and single-cell omics

seq2gex icon seq2gex

Learning how life's languages are expressed

simpletopics icon simpletopics

composite scores for indexed descriptions to target document(s)

stuck_in_plat icon stuck_in_plat

for the ave. apex legends player that needs to scheme to rank up

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