Manifold Interpolating Optimal-Transport Flows for Trajectory Inference. Article Swipe
Guillaume Huguet
,
D S Magruder
,
Alexander Tong
,
Oluwadamilola Fasina
,
Manik Kuchroo
,
Guy Wolf
,
Smita Krishnaswamy
·
YOU?
·
· 2022
· Open Access
·
YOU?
·
· 2022
· Open Access
·
We present a method called Manifold Interpolating Optimal-Transport Flow (MIOFlow) that learns stochastic, continuous population dynamics from static snapshot samples taken at sporadic timepoints. MIOFlow combines dynamic models, manifold learning, and optimal transport by training neural ordinary differential equations (Neural ODE) to interpolate between static population snapshots as penalized by optimal transport with manifold ground distance. Further, we ensure that the flow follows the geometry by operating in the latent space of an autoencoder that we call a geodesic autoencoder (GAE). In GAE the latent space distance between points is regularized to match a novel multiscale geodesic distance on the data manifold that we define. We show that this method is superior to normalizing flows, Schrödinger bridges and other generative models that are designed to flow from noise to data in terms of interpolating between populations. Theoretically, we link these trajectories with dynamic optimal transport. We evaluate our method on simulated data with bifurcations and merges, as well as scRNA-seq data from embryoid body differentiation, and acute myeloid leukemia treatment.
Related Topics
Concepts
Autoencoder
Ode
Geodesic
Ordinary differential equation
Manifold (fluid mechanics)
Population
Artificial neural network
Computer science
Mathematical optimization
Applied mathematics
Mathematics
Algorithm
Artificial intelligence
Mathematical analysis
Differential equation
Mechanical engineering
Demography
Sociology
Engineering
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://pubmed.ncbi.nlm.nih.gov/37397786
- OA Status
- green
- Cited By
- 24
- References
- 16
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4382918912
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4382918912Canonical identifier for this work in OpenAlex
- Title
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Manifold Interpolating Optimal-Transport Flows for Trajectory Inference.Work title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2022Year of publication
- Publication date
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2022-12-01Full publication date if available
- Authors
-
Guillaume Huguet, D S Magruder, Alexander Tong, Oluwadamilola Fasina, Manik Kuchroo, Guy Wolf, Smita KrishnaswamyList of authors in order
- Landing page
-
https://pubmed.ncbi.nlm.nih.gov/37397786Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://pmc.ncbi.nlm.nih.gov/articles/PMC10312391/pdf/nihms-1883152.pdfDirect OA link when available
- Concepts
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Autoencoder, Ode, Geodesic, Ordinary differential equation, Manifold (fluid mechanics), Population, Artificial neural network, Computer science, Mathematical optimization, Applied mathematics, Mathematics, Algorithm, Artificial intelligence, Mathematical analysis, Differential equation, Mechanical engineering, Demography, Sociology, EngineeringTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
24Total citation count in OpenAlex
- Citations by year (recent)
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2025: 10, 2024: 9, 2023: 5Per-year citation counts (last 5 years)
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16Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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