HAL (France)
open access
GraphDDP: a graph-embedding approach to detect differentiation pathways in single-cell-data using prior class knowledge
Abstract Cell types can be characterized by expression profiles derived from single-cell RNA-seq. Subpopulations are identified via clustering, yielding intuitive outcomes that can be validated by marker genes. Clustering, however, implies a discretization that cannot capture the continuous nature o
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- BEYOND GENE EXPRESSION: COMPUTATIONAL METHODS FOR ISOFORM AND CLONAL DYNAMICS IN SINGLE-CELL RNA SEQUENCING#929426
- LapDDPM: Spectral Perturbation Diffusion for Robust Single-Cell Manifold Generation#1104860
- The limits of scaling in aggregation-driven patterning of cell collectives#145692
- The limits of scaling in aggregation-driven patterning of cell collectives#141215
- Out of Distribution Generalization via Interventional Style Transfer in Single-Cell Microscopy.#358263
Record · ID 1219266
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive