Paper List
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Discovery of a Hematopoietic Manifold in scGPT Yields a Method for Extracting Performant Algorithms from Biological Foundation Model Internals
This work addresses the core challenge of extracting reusable, interpretable, and high-performance biological algorithms from the opaque internal repr...
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MS2MetGAN: Latent-space adversarial training for metabolite–spectrum matching in MS/MS database search
This paper addresses the critical bottleneck in metabolite identification: the generation of high-quality negative training samples that are structura...
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Toward Robust, Reproducible, and Widely Accessible Intracranial Language Brain-Computer Interfaces: A Comprehensive Review of Neural Mechanisms, Hardware, Algorithms, Evaluation, Clinical Pathways and Future Directions
This review addresses the core challenge of fragmented and heterogeneous evidence that hinders the clinical translation of intracranial language BCIs,...
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Less Is More in Chemotherapy of Breast Cancer
通过纳入细胞周期时滞和竞争项，解决了现有肿瘤-免疫模型的过度简化问题，以定量比较化疗方案。
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Fold-CP: A Context Parallelism Framework for Biomolecular Modeling
This paper addresses the critical bottleneck of GPU memory limitations that restrict AlphaFold 3-like models to processing only a few thousand residue...
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Open Biomedical Knowledge Graphs at Scale: Construction, Federation, and AI Agent Access with Samyama Graph Database
This paper addresses the core pain point of fragmented biomedical data by constructing and federating large-scale, open knowledge graphs to enable sea...
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Predictive Analytics for Foot Ulcers Using Time-Series Temperature and Pressure Data
This paper addresses the critical need for continuous, real-time monitoring of diabetic foot health by developing an unsupervised anomaly detection fr...
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Hypothesis-Based Particle Detection for Accurate Nanoparticle Counting and Digital Diagnostics
This paper addresses the core challenge of achieving accurate, interpretable, and training-free nanoparticle counting in digital diagnostic assays, wh...
使用QuPath和OMERO进行全切片和显微镜图像分析
Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
30秒速读
IN SHORT: 使QuPath能够直接分析存储在OMERO服务器中的图像而无需下载整个数据集，克服了大规模研究的本地存储限制。
核心创新
- Methodology Developed a new QuPath extension from scratch with three pixel access APIs (web, Ice, pixel data microservice) for flexible server compatibility
- Methodology Implemented unit testing with automated Docker container creation for OMERO server connections, ensuring software reliability
- Methodology Designed modular architecture separating core logic (headless operation) from GUI components, improving maintainability and scriptability
主要结论
- 自2024年2月以来，该扩展已被下载29,727次，显示了广泛的采用和活跃的用户社区。
- 支持高达20 GB未压缩的全切片图像（120,000 x 60,000像素）以及具有数十个16位/32位通道的荧光多重图像。
- 通过OMERO集成，能够访问包含超过400 TB已发布成像数据的IDR存储库。
摘要: QuPath是用于生物图像分析的开源软件。作为一个灵活且易于安装的桌面应用程序，QuPath被全球实验室用于可视化和分析大型复杂图像。然而，仅依赖存储在本地文件系统上的图像限制了QuPath在更大规模研究中的应用。本文描述了一个新的扩展，使QuPath能够从OMERO服务器访问像素和元数据。这通过允许软件高效处理远程存储的图像来增强其功能，同时也为希望将QuPath连接到其他图像管理系统的开发人员提供了模板。