arXiv AI August 3, 2026 By Omar Coser

ELISA: An Interpretable Hybrid Generative AI Agent for Expression-Grounded Discovery in Single-Cell Genomics

arXiv:2603. 11872v3 Announce Type: replace-cross Abstract: Translating single-cell RNA sequencing (scRNA-seq) data into mechanistic biological hypotheses remains a critical bottleneck, as agentic AI systems lack direct access to transcriptomic representations while expression foundation models remain opaque to natural language.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

arXiv Machine Learning

Jul 28

SCTA: An Agentic Framework for Stable and Interpretable Target Gene Discovery from Single-Cell RNA Sequencing

arXiv:2607. 23821v1 Announce Type: new Abstract: Identifying therapeutic target genes from single-cell RNA sequencing (scRNA-seq) data remains a fundamental challenge in translational biology.

By Shuyu Chen, Chen Zhu, Ye Zhang, Yang Li, Qiqi Xie, Haohan Wang

agents benchmarks safety

arXiv AI

Jun 26

scBench-Long: Verifiable Benchmarking of Long-Horizon Single-Cell Biology

arXiv:2606. 26563v1 Announce Type: cross Abstract: Single-cell studies require analysts to convert raw measurements into specific biological claims through multi-step workflows and integration of metadata, assay context, and auxiliary evidence.

By Ian Diks, Zhen Yang, Arjun Banerjee, Tim Proctor, Kenny Workman

agents benchmarks

arXiv Machine Learning

Sep 18

Transcriptomic Models for Immunotherapy Response Prediction Show Limited Cross-cohort Generalisability

The study evaluated nine transcriptomic models—five bulk RNA‑seq and four single‑cell RNA‑seq—designed to predict response to immune checkpoint inhibitors. Across independent datasets, bulk models performed near chance while single‑cell models offered only modest gains, and pathway analyses revealed inconsistent biomarker signals. The results highlight the limited cross‑cohort robustness and biological consistency of current transcriptomic ICI predictors.

By Yuheng Liang, Lucy Chhuo, Ahmadreza Argha, Nona Farbehi, Lu Chen, Roohallah Alizadehsani, Mehdi Hosseinzadeh, Min Yang, Thantrira Porntaveetusm, Youqiong Ye, Hamid Alinejad-Rokny

fine-tuning benchmarks

arXiv AI

Jun 4

BRAINCELL-AID: An Agentic AI Created Brain Cell Type Resource for Community Annotation

arXiv:2510. 17064v4 Announce Type: replace Abstract: Single-cell RNA sequencing has transformed our ability to identify diverse cell types and their transcriptomic signatures.

By Rongbin Li, Wenbo Chen, Zhao Li, Rodrigo Munoz-Castaneda, Jinbo Li, Neha S. Maurya, Arnav Solanki, Huan He, Hanwen Xing, Meaghan Ramlakhan, Zachary Wise, Nelson Johansen, Zhuhao Wu, Hua Xu, Michael Hawrylycz, W. Jim Zheng

llms rag agents safety

arXiv AI

Jun 18

SciHorizon-GENE: Benchmarking LLM for Life Sciences Inference from Gene Knowledge to Functional Understanding

arXiv:2601. 12805v4 Announce Type: replace-cross Abstract: Large language models (LLMs) have shown growing promise in biomedical research, particularly for knowledge-driven interpretation tasks.

By Xiaohan Huang, Meng Xiao, Chuan Qin, Qingqing Long, Jinmiao Chen, Yuanchun Zhou, Hengshu Zhu

llms benchmarks safety

arXiv AI

Jun 30

Data-Efficient Multimodal Alignment for Histopathology-based Molecular Prediction

arXiv:2606. 29949v1 Announce Type: cross Abstract: H&E-stained whole-slide images offer cohort-scale availability and rich spatial context but lack molecular specificity, whereas bulk RNA-seq provides transcriptome-wide resolution at high cost with limited archival availability.

By Dominik Winter, Dominik Vonficht, Lo\"ic Le Bescond, Christian Gebbe, Marco Rosati, Richard J. Chen, Markus Schick, Ross Stewart, Nicolas Brieu

llms fine-tuning multimodal safety

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Related stories

SCTA: An Agentic Framework for Stable and Interpretable Target Gene Discovery from Single-Cell RNA Sequencing

scBench-Long: Verifiable Benchmarking of Long-Horizon Single-Cell Biology

Transcriptomic Models for Immunotherapy Response Prediction Show Limited Cross-cohort Generalisability

BRAINCELL-AID: An Agentic AI Created Brain Cell Type Resource for Community Annotation

SciHorizon-GENE: Benchmarking LLM for Life Sciences Inference from Gene Knowledge to Functional Understanding

Data-Efficient Multimodal Alignment for Histopathology-based Molecular Prediction