Work

TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics

Year: 2020

Type: article

Abstract: , which controls the continuous paths taken between distributions to produce dynamic optimal transport. We show how this is particularly applicable for studying cellular dynamics in data from single-cell RNA sequencing (scRNA-seq) technologies, and that TrajectoryNet improves upon recently proposed static optimal transport-based models that can be used for interpolating cellular distributions.

Source: PubMed

DOI: 10.48550/arxiv.2002.04461

Authors: Tong, Alexander, Huang, Jessie, Wolf, Guy, van Dijk, David, Krishnaswamy, Smita

Institutions: Yale University, Mila - Quebec Artificial Intelligence Institute, Université de Montréal

Language: English

Topic: Single-cell and spatial transcriptomics

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: green

Funders: Institut de Valorisation des Données, National Institutes of Health, National Institute of General Medical Sciences, National Center for Advancing Translational Sciences

Awards: Deciphering Genetic and Epigenetic Regulatory Logic of Germ Layer Differentiation with Manifold Learning, Finding emergent structure in multi-sample biological data with the dual geometry of cells and features , Yale Clinical and Translational Science Award