When Seeing Is Not Believing: Understanding Uniform Manifold Approximation and Projection (UMAP) and t-Distributed Stochastic Neighbor Embedding (t-SNE) in Methylation-Based Tumor Classification
- DOI
- 10.1016/j.modpat.2026.101023
- Published
- 2026-08
- Container
- Modern Pathology
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.modpat.2026.101023,
title = {When Seeing Is Not Believing: Understanding Uniform Manifold Approximation and Projection (UMAP) and t-Distributed Stochastic Neighbor Embedding (t-SNE) in Methylation-Based Tumor Classification},
author = {Benjamin Emert},
year = {2026},
journal = {Modern Pathology},
doi = {10.1016/j.modpat.2026.101023},
url = {https://doi.org/10.1016/j.modpat.2026.101023}
}RIS
TY - JOUR TI - When Seeing Is Not Believing: Understanding Uniform Manifold Approximation and Projection (UMAP) and t-Distributed Stochastic Neighbor Embedding (t-SNE) in Methylation-Based Tumor Classification AU - Benjamin Emert PY - 2026 JO - Modern Pathology DO - 10.1016/j.modpat.2026.101023 UR - https://doi.org/10.1016/j.modpat.2026.101023 ER -
APA
Emert, B. (2026). When Seeing Is Not Believing: Understanding Uniform Manifold Approximation and Projection (UMAP) and t-Distributed Stochastic Neighbor Embedding (t-SNE) in Methylation-Based Tumor Classification. Modern Pathology. https://doi.org/10.1016/j.modpat.2026.101023
Source records
- crossref · retrieved 2026-11-10T16:44:54.305Z