Sarah Nyquist

Former Graduate Student

Degrees & Affiliations

BA, Computer Science - Rice University PhD Candidate, Computational & Systems Biology - MIT

Background & Interests

Biography

Sarah is a third year graduate student in the Computational and Systems Biology
program co-advised by Professors Alex Shalek and Bonnie Berger. She is interested
in applying machine learning methods to better understand single cell genomic
data.

Before starting at MIT, Sarah studied computer science at Rice University where
she worked on genome assembly algorithms. In her free time Sarah likes to
explore art museums, make crafts, and go for very slow runs.

Publications

CD4+ T cells re-wire granuloma cellularity and regulatory networks to promote immunomodulation following Mtb reinfection

Bromley et al.,
Immunity,
2024

Systematic deconstruction of myeloid cell signaling in tuberculosis granulomas reveals IFN-γ, TGF-β, and time are associated with conserved myeloid diversity

Peters et al.,
biorxiv,
2024

CD4 + T cells are homeostatic regulators during Mtb reinfection

Bromley et al.,
bioRxiv,
2024

CD8+ lymphocytes are critical for early control of tuberculosis in macaques

Winchell et al.,
Journal of Experimental Medicine,
2023

Identification and characterization of the T cell receptor (TCR) repertoire of the cynomolgus macaque (Macaca Fascicularis)

Jaiswal et al.,
BMC Genomics,
2023

HIV specific CD8+ TRM-like cells in tonsils express exhaustive signatures in the absence of natural HIV control

Fardoos et al.,
Frontiers in Immunology,
2023

Multimodal profiling of lung granulomas in macaques reveals cellular correlates of tuberculosis control

Gideon et al.,
Immunity,
2022

Cellular and transcriptional diversity over the course of human lactation

Nyquist et al.,
PNAS,
2022

HIV infection drives interferon signaling within intestinal SARS-CoV-2 target cells

Fardoos et al.,
JCI Insight,
2021

Human airway mast cells proliferate and acquire distinct inflammation-driven phenotypes during type 2 inflammation

Dwyer et al.,
Science Immunology,
2021