References

Bergen20

Bergen, V. et al. (2020), Generalizing RNA velocity to transient cell states through dynamical modeling, Nature Biotechnology.

Coifman05

Coifman et al. (2005), Geometric diffusions as a tool for harmonic analysis and structure definition of data: Diffusion maps, PNAS.

GPCCA18

Reuter, B. et al. (2018), Generalized Markov State Modeling Method for Nonequilibrium Biomolecular Dynamics: Exemplified on Amyloid β Conformational Dynamics Driven by an Oscillating Electric Field., Journal of Chemical Theory and Computation.

Haghverdi16

Haghverdi et al. (2016), Diffusion pseudotime robustly reconstructs branching cellular lineages, Nature Methods.

Li2020

Li, T. et al. (2020), On the Mathematics of RNA Velocity I: Theoretical Analysis, bioRxiv.

Lung20

Strunz, M. et al. (2020), Alveolar regeneration through a Krt8+ transitional stem cell state that persists in human lung fibrosis, Nature Communications.

Macosko15

Macosko, E. Z. et al., (2015), Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets, Cell.

MAGIC18

Van Dijk, D. et al. (2018), Recovering Gene Interactions from Single-Cell Data Using Data Diffusion, Cell.

Manno18

La Manno et al. (2018), RNA velocity of single cells, Nature.

Morris18

Biddy, B.A., Kong, W., Kamimoto, K. et al. (2018), Single-cell mapping of lineage and identity in direct reprogramming., Nature 564, 219–224.

Panc19

Bastidas-Ponce et al. (2019), Comprehensive single cell mRNA profiling reveals a detailed roadmap for pancreatic endocrinogenesis, Development.

Reuter19

Reuter, B. et al. (2019), Generalized Markov modeling of nonreversible molecular kinetics, The Journal of Chemical Physics.

Robinson10

Robinson, M. D. et al. (2010), A scaling normalization method for differential expression analysis of RNA-seq data, Genome Biology.

Setty19

Setty et al. (2019), Characterization of cell fate probabilities in single-cell data with Palantir, Nature Biotechnology.

Tolver16

Tolver (2016), An introduction to Markov chains, Recuperado el 15.

Weinreb18

Weinreb et al. (2018), Fundamental limits on dynamic inference from single-cell snapshots, PNAS.

Wolf18

Wolf et al. (2018), Scanpy: large-scale single-cell gene expression data analysis, Genome Biology.

Wolf19

Wolf et al. (2019), PAGA: Graph abstraction reconciles clustering with trajectory inference through a topology preserving map of single cells, Genome Biology.