Author

Nathaniel Scott

Princeton University

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

Click to filter author papers

Bioinformatics· 1 Neuroscience· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Research Focus:batch correction / integration· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Approach:deep learning· 1 Research Focus:dimensionality reduction· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1 Organism:mouse· 1

Frequent Co-Authors

Changkyu LeeiD· 2 shared Christopher CardenasiD· 2 shared David Turner· 2 shared Fenna M. KrieneniD· 2 shared Hannah Feinberg· 2 shared Jessica Schembri· 2 shared Jonathan W. PillowiD· 2 shared Lakme CaceresiD· 2 shared

Activity by Year

2025-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

2 shared papersBioinformatics

Changkyu LeeORCID

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

PIANO: Probabilistic Inference Autoencoder Networks for multi-Omics enables robust generative modeling of gene expression and scales single-cell integration to 100 million cells

Ning Wang, Christopher Cardenas, Victor Eduardo Nieto Caballero, David Turner, Hannah Feinberg, Dan Yuan, Nathaniel Scott, Michael DeBerardine, Shu Dan, Lakme Caceres, Jessica Schembri, Zizhen Yao, Changkyu Lee, Jonathan W. Pillow, Fenna M. Krienen

PIANO integrates single-cell data across species and modalities, models gene expression, and scales to 100 million cells for drug perturbation analysis.

bioRxiv · Aug 12, 2026 · PreprintBioinformatics

Fast Optimization of Robust Transcriptomics Embeddings using Probabilistic Inference Autoencoder Networks for multi-Omics

Ning Wang, David Turner, Hannah Feinberg, Victor Eduardo Nieto Caballero, Dan Yuan, Nathaniel Scott, Christopher Cardenas, Michael DeBerardine, Shu Dan, Lakme Caceres, Jessica Schembri, Zizhen Yao, Changkyu Lee, Jonathan W. Pillow, Fenna M. Krienen

The paper introduces PIANO, a variational autoencoder for multi-omics integration, showing improved performance on single-species and multi-atlas datasets.

bioRxiv · Nov 16, 2025 · PreprintNeuroscience