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Nir Yosef

Researcher at University of California, Berkeley

Publications -  212
Citations -  22154

Nir Yosef is an academic researcher from University of California, Berkeley. The author has contributed to research in topics: Gene & Cellular differentiation. The author has an hindex of 48, co-authored 190 publications receiving 15732 citations. Previous affiliations of Nir Yosef include UCB & Brigham and Women's Hospital.

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The Human Cell Atlas

Aviv Regev, +81 more
- 05 Dec 2017 - 
TL;DR: An open comprehensive reference map of the molecular state of cells in healthy human tissues would propel the systematic study of physiological states, developmental trajectories, regulatory circuitry and interactions of cells, and also provide a framework for understanding cellular dysregulation in human disease.
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Slingshot: cell lineage and pseudotime inference for single-cell transcriptomics

TL;DR: Slingshot is a uniquely robust and flexible tool which combines the highly stable techniques necessary for noisy single-cell data with the ability to identify multiple trajectories and infers more accurate pseudotimes than other leading methods.
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Single-cell transcriptomics reveals bimodality in expression and splicing in immune cells

TL;DR: The authors used single-cell RNA-Seq to investigate heterogeneity in the response of bone marrow derived dendritic cells (BMDCs) to lipopolysaccharide (LPS) and found extensive, and previously unobserved, bimodal variation in mRNA abundance and splicing patterns.
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Sodium chloride drives autoimmune disease by the induction of pathogenic TH17 cells

TL;DR: It is shown that increased salt concentrations found locally under physiological conditions in vivo markedly boost the induction of murine and human TH17 cells, which display a highly pathogenic and stable phenotype characterized by the upregulation of the pro-inflammatory cytokines GM-CSF, TNF-α and IL-2.
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Deep generative modeling for single-cell transcriptomics.

TL;DR: Single-cell variational inference (scVI) is a ready-to-use generative deep learning tool for large-scale single-cell RNA-seq data that enables raw data processing and a wide range of rapid and accurate downstream analyses.