Y
Ying Tang
Researcher at Shanghai Jiao Tong University
Publications - 35
Citations - 2731
Ying Tang is an academic researcher from Shanghai Jiao Tong University. The author has contributed to research in topics: Multiplicative noise & Computer science. The author has an hindex of 11, co-authored 26 publications receiving 1608 citations. Previous affiliations of Ying Tang include University of California, Los Angeles & University of California, San Diego.
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Journal ArticleDOI
Reversed graph embedding resolves complex single-cell trajectories.
TL;DR: Monocle 2, an algorithm that uses reversed graph embedding to describe multiple fate decisions in a fully unsupervised manner, is applied to two studies of blood development and found that mutations in the genes encoding key lineage transcription factors divert cells to alternative fates.
Journal ArticleDOI
Chemotaxis as a navigation strategy to boost range expansion
Jonas Cremer,Jonas Cremer,Tomoya Honda,Tomoya Honda,Ying Tang,Jerome Wong-Ng,Massimo Vergassola,Terence Hwa +7 more
TL;DR: This work identifies an alternative role of chemotaxis by systematically examining the spatiotemporal dynamics of Escherichia coli in soft agar and concludes that this process of navigated range expansion spreads faster and yields larger population gains than unguided expansion following the canonical Fisher–Kolmogorov dynamics.
Posted ContentDOI
Reversed graph embedding resolves complex single-cell developmental trajectories
TL;DR: Monocle 2 is presented, which uses reversed graph embedding to reconstruct single-cell trajectories in a fully unsupervised manner and uncovered a new, alternative cell fate in what was previously reported to be a linear trajectory for differentiating myoblasts.
Journal ArticleDOI
Potential landscape of high dimensional nonlinear stochastic dynamics with large noise
TL;DR: In this article, the relative probabilities between locally stable states of high-dimensional nonequilibrium systems are computed based on a least action method without the necessity of simulating the steady-state distribution.
Journal ArticleDOI
Summing over trajectories of stochastic dynamics with multiplicative noise.
Ying Tang,Ruoshi Yuan,Ping Ao +2 more
TL;DR: This work develops a novel path integral formulation for the overdamped Langevin equation with multiplicative noise that solves the inconsistency of the previous path integral formulations for the general stochastic interpretation, and can have wide applications in chemical and physical Stochastic processes.