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  • Artificial Intelligence Facilitates Tissue Substructure Identification from Spatial Resolved Transcriptomics

    A research team led by Prof. ZHANG Shihua from the Academy of Mathematics and Systems Science has proposed a new computational tool, STAGATE, to decipher tissue substructures from spatial resolved transcriptomics. The model uses artificial intelligence technology to integrate spatial location information and gene expression profile of spatial spots. In this algorithm, a graph attention autoencoder is introduced, with a graph attention mechanism in the middle hidden layer, which can learn the heterogeneous similarities between neighboring spots adaptively.

    Apr 02, 2022
  • Researchers Prove Global Smoothness for Monge-Ampère Equation

    Prof. CHEN Shibing from University of Science and Technology of China (USTC) of the Chinese Academy of Sciences and his collaborators have studied the global regularity for the Monge-Ampère equation with natural boundary condition.

    Aug 29, 2021
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