Shengyu Li

Shengyu Li

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A list of all the posts and pages found on the site. For you robots out there, there is an XML version available for digesting as well.

Pages

Posts

Future Blog Post

less than 1 minute read

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Blog Post number 4

less than 1 minute read

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Blog Post number 3

less than 1 minute read

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Blog Post number 2

less than 1 minute read

Published:

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Blog Post number 1

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

portfolio

publications

A relay velocity model infers cell-dependent RNA velocity (Nature Biotechnology)

April 03, 2023

RNA velocity provides an approach for inferring cellular state transitions from single-cell RNA sequencing (scRNA-seq) data. Conventional RNA velocity models infer universal kinetics from all cells in an scRNA-seq experiment, resulting in unpredictable performance in experiments with multi-stage and/or multi-lineage transition of cell states where the assumption of the same kinetic rates for all cells no longer holds. Here we present cellDancer, a scalable deep neural network that locally infers velocity for each cell from its neighbors and then relays a series of local velocities to provide single-cell resolution inference of velocity kinetics. In the simulation benchmark, cellDancer shows robust performance in multiple kinetic regimes, high dropout ratio datasets and sparse datasets. We show that cellDancer overcomes the limitations of existing RNA velocity models in modeling erythroid maturation and hippocampus development. Moreover, cellDancer provides cell-specific predictions of transcription, splicing and degradation rates, which we identify as potential indicators of cell fate in the mouse pancreas.

Shengyu Li, Pengzhi Zhang, Weiqing Chen, Lingqun Ye, Kristopher W. Brannan, Nhat-Tu Le, Jun-ichi Abe, John P. Cooke & Guangyu Wang
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An ERK5-NRF2 Axis Mediates Senescence-Associated Stemness and Atherosclerosis (Circulation Research)

June 23, 2023

We discovered a novel mechanism by which the macrophage ERK5-NRF2 axis develops a unique senescence-associated secretory phenotype/stemness phenotype by upregulating AHR to engender atherogenesis. The finding of senescence-associated stemness phenotype provides a molecular explanation to resolve the paradox of senescence in proliferative plaque by permitting myeloid cells to escape the senescence-induced cell cycle arrest during atherosclerosis formation.

Jun-ichi Abe#, Masaki Imanishi#, Shengyu Li#, Aijun Zhang, Kyung Ae Ko, Venkata S.K. Samanthapudi, Ling-Ling Lee, Angelica Paniagua Bojorges, Young Jin Gi, Brian P. Hobbs, Anita Deswal, Joerg Herrmann, Steven H. Lin, Eduardo N. Chini, Ying H. Shen, Keri L. Schadler, Thi-Hong-Minh Nguyen, Anisha A. Gupte, Cielito Reyes-Gibby, Sai-Ching J. Yeung, Rei J. Abe, Elizabeth A. Olmsted-Davis, Sunil Krishnan, Robert Dantzer, Nicolas L. Palaskas, John P. Cooke, Henry J. Pownall, Momoko Yoshimoto, Keigi Fujiwara, Dale J. Hamilton, Jared K. Burks, Guangyu Wang*, Nhat-Tu Le* and Sivareddy Kotla*
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Paper Title Number 4

, 2024

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talks

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015

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