Article

A Biologically Grounded Structural Causal Model Enables cfRNA Specific In-Context Learning

2025-12-13

Abstract excerpt

Cell-free RNA (cfRNA) in human plasma provides a minimally invasive readout of tissue physiology, yet its extreme sparsity, heavy-tailed abundance distributions, and weak but structured correlation patterns create major challenges for machine learning. Conventional tabular foundation models are typically trained on synthetic datasets that assume generic statistical properties, and as a result, they fail to capture...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: c60316e1-2705-5a5e-84e0-24ffd5876cc7
DOI: 10.64898/2025.12.10.693604

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

A Biologically Grounded Structural Causal Model Enables cfRNA Specific In-Context LearningDOI 10.64898/2025.12.10.693604Read

A multi-modal cell-free RNA language model for liquid biopsy applicationsSemantic proximity Read

Learning to Estimate Sample-specific Transcriptional Networks for 7000 TumorsSemantic proximity Read

Quantized multi-task learning for context-specific representations of gene network dynamicsSemantic proximity Read

Scaling Dense Representations for Single Cell with Transcriptome-Scale ContextSemantic proximity Read

mcBERT: Patient-Level Single-cell Transcriptomics Data RepresentationSemantic proximity Read

scRegulate: Single-Cell Regulatory-Embedded Variational Inference of Transcription Factor Activity from Gene ExpressionSemantic proximity Read

BoYueGRN: Zero-shot causal discovery of directed gene regulatory networks from single-cell transcriptomes via amortized inference over synthetic structural causal modelsSemantic proximity Read

RNABag: A Generalizable Transcriptome Foundation Model for Precision Oncology across Biopsy ModalitiesSemantic proximity Read

GeneBag: training a cell foundation model for broad-spectrum cancer diagnosis and prognosis with bulk RNA-seq dataSemantic proximity Read

AetherCell: A generative engine for virtual cell perturbation and <i>in vivo</i> drug discoverySemantic proximity Read

Parameter-free representations outperform single-cell foundation models on downstream benchmarksSemantic proximity Read

TRAILBLAZER: generative multicellular perturbation model of biologySemantic proximity Read