Cover Image

scGSDR: Harnessing Gene Semantics for Single-Cell Pharmacological Profiling

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Huang, Yu-An, Cao, Xiyue, You, Zhu-Hong, Li, Yue-Chao, Shang, Xuequn, Huang, Zhi-An
Format:	Preprint
Published:	2025
Subjects:	Genomics Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data
by: Huang, Yu-An, et al.
Published: (2025)

scBench: Evaluating AI Agents on Single-Cell RNA-seq Analysis
by: Workman, Kenny, et al.
Published: (2026)

scUnified: An AI-Ready Standardized Resource for Single-Cell RNA Sequencing Analysis
by: Xu, Ping, et al.
Published: (2025)

scCluBench: Comprehensive Benchmarking of Clustering Algorithms for Single-Cell RNA Sequencing
by: Xu, Ping, et al.
Published: (2025)

scPilot: Large Language Model Reasoning Toward Automated Single-Cell Analysis and Discovery
by: Gao, Yiming, et al.
Published: (2026)

scInterpreter: Training Large Language Models to Interpret scRNA-seq Data for Cell Type Annotation
by: Li, Cong, et al.
Published: (2024)

Gene Incremental Learning for Single-Cell Transcriptomics
by: Qi, Jiaxin, et al.
Published: (2025)

SpaDiT: Diffusion Transformer for Spatial Gene Expression Prediction using scRNA-seq
by: Li, Xiaoyu, et al.
Published: (2024)

scASDC: Attention Enhanced Structural Deep Clustering for Single-cell RNA-seq Data
by: Min, Wenwen, et al.
Published: (2024)

Learning to Discover Regulatory Elements for Gene Expression Prediction
by: Su, Xingyu, et al.
Published: (2025)

Knowledge-Guided Biomarker Identification for Label-Free Single-Cell RNA-Seq Data: A Reinforcement Learning Perspective
by: Xiao, Meng, et al.
Published: (2025)

scReader: Prompting Large Language Models to Interpret scRNA-seq Data
by: Li, Cong, et al.
Published: (2024)

Enhanced Gene Selection in Single-Cell Genomics: Pre-Filtering Synergy and Reinforced Optimization
by: Zhang, Weiliang, et al.
Published: (2024)

xTrimoGene: An Efficient and Scalable Representation Learner for Single-Cell RNA-Seq Data
by: Gong, Jing, et al.
Published: (2023)

Bridging Large Language Models and Single-Cell Transcriptomics in Dissecting Selective Motor Neuron Vulnerability
by: Jiang, Douglas, et al.
Published: (2025)

A Versatile AI Agent for Rare Disease Diagnosis and Risk Gene Prioritization
by: Liu, Tianyu, et al.
Published: (2026)

Gene-R1: Reasoning with Data-Augmented Lightweight LLMs for Gene Set Analysis
by: Wang, Zhizheng, et al.
Published: (2025)

Meta-Learning on Augmented Gene Expression Profiles for Enhanced Lung Cancer Detection
by: Moghaddam, Arya Hadizadeh, et al.
Published: (2024)

Single Cells Are Spatial Tokens: Transformers for Spatial Transcriptomic Data Imputation
by: Wen, Hongzhi, et al.
Published: (2023)

ELISA: An Interpretable Hybrid Generative AI Agent for Expression-Grounded Discovery in Single-Cell Genomics
by: Coser, Omar
Published: (2026)

PathGene: Benchmarking Driver Gene Mutations and Exon Prediction Using Multicenter Lung Cancer Histopathology Image Dataset
by: Pan, Liangrui, et al.
Published: (2025)

CellxPert: Inference-Time MCMC Steering of a Multi-Omics Single-Cell Foundation Model for In-Silico Perturbation
by: Demir, Andac, et al.
Published: (2026)

scSiameseClu: A Siamese Clustering Framework for Interpreting single-cell RNA Sequencing Data
by: Xu, Ping, et al.
Published: (2025)

Survey and Improvement Strategies for Gene Prioritization with Large Language Models
by: Neeley, Matthew, et al.
Published: (2025)

Systematic Evaluation of Single-Cell Foundation Model Interpretability Reveals Attention Captures Co-Expression Rather Than Unique Regulatory Signal
by: Kendiukhov, Ihor
Published: (2026)

scI2CL: Effectively Integrating Single-cell Multi-omics by Intra- and Inter-omics Contrastive Learning
by: Liu, Wuchao, et al.
Published: (2025)

Lingshu-Cell: A generative cellular world model for transcriptome modeling toward virtual cells
by: Zhang, Han, et al.
Published: (2026)

scCDCG: Efficient Deep Structural Clustering for single-cell RNA-seq via Deep Cut-informed Graph Embedding
by: Xu, Ping, et al.
Published: (2024)

Leveraging Gene Expression Data and Explainable Machine Learning for Enhanced Early Detection of Type 2 Diabetes
by: Roy, Aurora Lithe, et al.
Published: (2024)

CRADLE-VAE: Enhancing Single-Cell Gene Perturbation Modeling with Counterfactual Reasoning-based Artifact Disentanglement
by: Baek, Seungheun, et al.
Published: (2024)

LA-MARRVEL: A Knowledge-Grounded, Language-Aware LLM Framework for Clinically Robust Rare Disease Gene Prioritization
by: Lee, Jaeyeon, et al.
Published: (2025)

GeneSUM: Large Language Model-based Gene Summary Extraction
by: Chen, Zhijian, et al.
Published: (2024)

Celler:A Genomic Language Model for Long-Tailed Single-Cell Annotation
by: Zhao, Huan, et al.
Published: (2025)

Multi-Dimensional Spectral Geometry of Biological Knowledge in Single-Cell Transformer Representations
by: Kendiukhov, Ihor
Published: (2026)

Nano Bio-Agents (NBA): Small Language Model Agents for Genomics
by: Hong, George, et al.
Published: (2025)

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis
by: Huang, Yu-An, et al.
Published: (2025)

Knowledge-guided Contextual Gene Set Analysis Using Large Language Models
by: Wang, Zhizheng, et al.
Published: (2025)

Toward a Team of AI-made Scientists for Scientific Discovery from Gene Expression Data
by: Liu, Haoyang, et al.
Published: (2024)

VQDNA: Unleashing the Power of Vector Quantization for Multi-Species Genomic Sequence Modeling
by: Li, Siyuan, et al.
Published: (2024)

CellMaster: Collaborative Cell Type Annotation in Single-Cell Analysis
by: Wang, Zhen, et al.
Published: (2026)