scRNA-RAGent
An autonomous single-cell analyst project for comprehensive single-cell RNA sequencing data processing and marker gene identification.
Updated: March 2026
Open-source frameworks, datasets, and translational AI systems developed to support reproducible bioinformatics research.
An autonomous single-cell analyst project for comprehensive single-cell RNA sequencing data processing and marker gene identification.
A sustainable AI framework optimizing Carbon Efficiency Score in deep learning models for eco-friendly computing.
Intrusion Detection System for edge networks utilizing the CIC-IDS2017 dataset.
Applying Vision Transformers for accurate medical image segmentation and low-light enhancement.
Utilizing Genomic Signal Processing techniques for identifying novel cancer subtypes.
A robust computational workflow to evaluate and improve imputation quality in spatial transcriptomics using advanced AI models.
Predictive framework uncovering hidden snoRNA-disease associations using graph theory and machine learning.
Integrating Large Language Models (LLMs) with Retrieval-Augmented Generation (RAG) for natural language querying of multi-omics databases.
A state-of-the-art diffusion-based neural network architecture for structure-based drug design.
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