single-cell RNA-seq
PulseAugur coverage of single-cell RNA-seq — every cluster mentioning single-cell RNA-seq across labs, papers, and developer communities, ranked by signal.
4 天有情绪数据
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新的scFM方法模拟单细胞基因表达动力学
研究人员开发了一个名为单细胞流匹配（scFM）的新框架，以更好地模拟单细胞中基因表达的动力学。该方法解决了现有技术中的挑战，例如离散时间点之间转换的模糊性以及长期预测中的误差累积。通过使用条件流匹配和双向速度场，scFM提高了时间插值和外推的准确性，从而更忠实地重建基因表达动力学。
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New framework estimates continuous dynamics from discrete data snapshots
Researchers have developed a new framework called CT-OT Flow to estimate continuous-time dynamics from discrete, aggregated data snapshots. This method addresses challenges like noisy timestamps and the absence of conti…
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New framework models temporal single-cell RNA data with Gaussian process and optimal transport
Researchers have developed a new generative framework to model temporal processes in single-cell RNA sequencing data. This approach utilizes a latent heteroscedastic Gaussian process, approximated via Hilbert space meth…
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scHelix framework improves single-cell RNA sequencing data integration
Researchers have introduced scHelix, a novel framework designed to improve the integration of single-cell RNA sequencing data. This method addresses the challenge of removing batch effects while preserving crucial biolo…
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新的基准测试通过供体感知scRNA-seq分析改进了IBD分类
研究人员开发了一种用于使用单细胞RNA测序（scRNA-seq）数据分类炎症性肠病（IBD）的供体感知基准测试。该新基准测试通过确保训练和测试数据来自不同的供体，解决了假复制问题。该研究评估了三种特征表示，包括居中对数比（CLR）转换的细胞类型组成和GatedStructuralCFN依赖性嵌入，跨越两个独立的IBD队列。
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New HyCNNs architecture offers improved convex function learning and optimal transport
Researchers have developed Hyper Input Convex Neural Networks (HyCNNs), a new architecture designed to learn convex functions more efficiently than existing Input Convex Neural Networks (ICNNs). HyCNNs integrate Maxout …