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Stephen R. Quake
Researcher at Stanford University
Publications - 626
Citations - 89247
Stephen R. Quake is an academic researcher from Stanford University. The author has contributed to research in topics: Transcriptome & Biology. The author has an hindex of 132, co-authored 589 publications receiving 77778 citations. Previous affiliations of Stephen R. Quake include Agency for Science, Technology and Research & Allegheny Health Network.
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Human IgE producing B cells have a unique transcriptional program and generate high affinity, allergen-specific antibodies
TL;DR: The isolation of IgE producing B cells from the blood of individuals with food allergies is described, followed by a detailed study of their properties by single cell RNA sequencing (scRNA-seq), and splicing within B cells of all isotypes reveals polarized germline transcription of the IgE, but not IgG4, isotype.
Journal ArticleDOI
At the interface of physics and biology.
TL;DR: I grew up during the personal computer revolution and spent a lot of time programming computers and building things that interfaced with them, and I tried to make a career at the interface of the two fields.
Posted ContentDOI
Inhibiting USP16 rescues stem cell aging and memory in an Alzheimer's model
Felicia Reinitz,Elizabeth H. Chen,Benedetta Nicolis di Robilant,Bayarsaikhan Chuluun,Jane Antony,Robert C. Jones,Neha Gubbi,Sai Saroja Kolluru,Dalong Qian,Katja Piltti,Aileen Anderson,Michelle Monje,H. Craig Heller,Stephen R. Quake,Michael F. Clarke +14 more
TL;DR: In this paper, a mouse model of Alzheimer's disease and human fetal cells harboring mutant amyloid precursor protein was used to identify an earlier targetable phenotype and demonstrate that reversing impaired intrinsic neural precursor cell self-renewal via genetic reduction of USP16, a histone modifier and critical physiological antagonist of the Polycomb Repressor Complex 1, can prevent downstream cognitive defects and decrease astrogliosis in vivo.
Posted ContentDOI
Northstar enables automatic classification of known and novel cell types from tumor samples
Fabio Zanini,Bojk A. Berghuis,Robert C. Jones,Benedetta Nicolis di Robilant,Rachel Yuan Nong,Jeffrey A. Norton,Michael F. Clarke,Stephen R. Quake +7 more
TL;DR: In this paper, the authors developed a computational approach to classify thousands of cells based on published data within seconds while simultaneously identifying and highlighting new cell states such as malignancies, and tested it on human glioblastoma and melanoma and obtained high accuracy and robustness.
Posted ContentDOI
Aging causes changes in transcriptional noise across a diverse set of cell types
TL;DR: A quantitative, well-calibrated statistical model of single-cell RNAseq measurement is developed from which a sensitively detected changes in gene expression noise, a measure of cellular heterogeneity, across age and many cell types and tissues.