Hugging Face Trending Papers September 2, 2026

Subcellularly Resolved Single-Cell Embedding Learning with Transcriptomic data, Protein Structure and Localization Information

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The paper introduces a multimodal framework that learns subcellularly resolved cell embeddings by integrating RNA expression profiles, protein sequence representations, and protein structural information. It uses a cross‑attention architecture to model interactions across distinct subcellular compartments, producing embeddings that capture both molecular expression patterns and functional protein properties. This approach is presented as the first to jointly incorporate transcriptomic data, protein sequences, and structural knowledge within a unified cross‑modal learning paradigm.

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arXiv AI

Sep 3

Subcellularly Resolved Single-Cell Embedding Learning with Transcriptomic data, Protein Structure and Localization Information

The paper introduces a multimodal framework that learns subcellularly resolved cell embeddings by integrating RNA expression profiles, protein sequence representations, and protein structural information using a cross‑attention architecture. This approach models interactions within distinct subcellular compartments, producing fine‑grained embeddings that capture both molecular expression patterns and functional protein properties. It is presented as the first method to jointly incorporate transcriptomic data, sequence, and structural knowledge for subcellularly resolved cell representation.

By Zhen Zhou, Jiachen Li, Yuan Liu, Xiaoyong Pan, Hong-Bin Shen

rag multimodal

arXiv AI

2d ago

CellMSA: Context Modeling for Single-Cell Representation Learning

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efficiency benchmarks safety

arXiv AI

Aug 5

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rag multimodal safety

arXiv AI

Jun 12

scLLM-DSC: LLM-Knowledge Enhanced Cross-Modal Deep Structural Clustering for Single-Cell RNA Sequencing

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llms rag diffusion multimodal benchmarks safety

arXiv AI

Jun 3

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arXiv:2606. 02629v1 Announce Type: cross Abstract: Protein-protein interactions (PPIs) are essential for many biological processes.

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rag multimodal benchmarks

arXiv Machine Learning

1d ago

Prototype Guided Post-pretraining for Single-Cell Representation Learning

arXiv:2605.07938v2 Announce Type: replace Abstract: Single-cell representation learning (SCRL) from gene expression data offers a way to uncover the complex regulatory logic underlying cellular funct...

By Sachini Weerasekara, Natasha Darras, Sagar Kamarthi, Colles Price, Jacqueline Isaacs

llms rag fine-tuning

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Subcellularly Resolved Single-Cell Embedding Learning with Transcriptomic data, Protein Structure and Localization Information

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