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May 23, 2024Briefings in BioinformaticsOpen Access

A multi-view graph contrastive learning framework for deciphering spatially resolved transcriptomics data

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Authors

LZLei ZhangSLShu LiangLWLin Wan

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Cite This Study

Zhang et al. (2024) studied this question.

synapsesocial.com/papers/68e68ab2b6db6435876129edhttps://doi.org/10.1093/bib/bbae255
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1MuCST: restoring and integrating heterogeneous morphology images and spatial transcriptomics data with contrastive learning2024
  2. 2CoCo-ST: Comparing and Contrasting Spatial Transcriptomics data sets using graph contrastive learning2024
  3. 3MGCL-ST: multi-view graph contrastive learning for spatial transcriptomics imputation2026
  4. 4Dual-contrastive learning for spatial domain identification in spatial transcriptomics with STAMGC2026
  5. 5Biased multi-view contrastive learning with attentive masking for spatial transcriptomic analysis2026