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  • GitHub - KrishnaswamyLab PHATE: PHATE (Potential of Heat-diffusion for . . .
    PHATE (Potential of Heat-diffusion for Affinity-based Trajectory Embedding) is a tool for visualizing high dimensional data PHATE uses a novel conceptual framework for learning and visualizing the manifold to preserve both local and global distances
  • PHATE - Potential of Heat-diffusion for Affinity-based Trajectory . . .
    PHATE (Potential of Heat-diffusion for Affinity-based Trajectory Embedding) is a tool for visualizing high dimensional data PHATE uses a novel conceptual framework for learning and visualizing the manifold to preserve both local and global distances
  • NBT：单细胞转录组新降维可视化方法PHATE - 知乎
    PHATE除了可以应用于单细胞分析，还适用于很多数据类型，如 质谱数据 、Hi-C数据和 肠道菌群 数据等。 PHATE算法主要为三个步骤： 通过局部相似性对局部数据信息进行编码； 使用潜在距离在数据中编码全局关系； 将潜在距离信息嵌入低维度以进行可视化；
  • 使用PHATE进行单细胞高维数据的可视化 - 简书
    简介 PHATE (Potential of Heat-diffusion for Affinity-based Transition Embedding) 是Krishnaswamy实验室开发的一种用于可视化具有自然进程或轨迹的高维单细胞数据的工具。 PHATE 使用一种新颖的概念框架来学习和可视化生物系统中固有的流形。
  • 每天一篇单细胞38-- PHATE - 知乎
    提取继续打卡，今天这篇的题目是：Visualizing structure and transitions in high-dimensional biological data，介绍了一个降维并可视化的方法PHATE。 首先是该方法的总体介绍： Overview of PHATE and its ability to reveal structure in data
  • PHATE - Krishnaswamy Lab
    In this paper, we present PHATE (Potential of Heat-diffusion for Affinity-based Transition Embedding) - an unsupervised low-dimensional embedding for visualization of data that is aimed at solving these issues
  • 3. Visualizing data using PHATE - Krishnaswamy Lab
    To use PHATE, you must first instantiate a phate PHATE object, and then use fit_transform to build a graph to your data and reduce the dimensionality of the data for visualization
  • phate. phate — PHATE 1. 0. 11 documentation - Read the Docs
    Potential of Heat-diffusion for Affinity-based Trajectory Embedding (PHATE) embeds high dimensional single-cell data into two or three dimensions for visualization of biological progressions as described in Moon et al, 2017 [1]_
  • Visualizing structure and transitions in high-dimensional biological . . .
    We present PHATE, a visualization method that captures both local and global nonlinear structure using an information-geometric distance between data points
  • PHATE：基于热扩散势与亲和力的高维生物数据流形可视化工具
    PHATE（Potential of Heat-diffusion for Affinity-based Transition Embedding，基于亲和力的过渡嵌入的热扩散势）是一种前沿、理论严谨且实践性强的高维数据可视化与降维方法，专为揭示复杂生物系统中隐含的动态结构、连续轨迹与非线性流形而设计。





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