Reproducing result from the paper
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Singapore, Singapore
MCA

数据描述

Reproducing result from the paper

All datasets are available in this drive directory. All latent space represenstations and pre-trained models are available in this drive directory.

github.com
IP: 20.205.243.166
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相关论文

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Mapping single-cell data to reference atlases by transfer learning

Lotfollahi MohammadNaghipourfar MohsenLuecken Malte D.Khajavi MatinBüttner Maren13
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00 p.1-10
Large single-cell atlases are now routinely generated to serve as references for analysis of smaller-scale studies. Yet learning from reference data is complicated by batch effects between datasets, limited availability of computational resources and sharing restrictions on raw data. Here we introdu...
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Nature Computational Science
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00 p.1-17
Understanding gene spatial expression and the organization of multicellular systems is vital for disease diagnosis and studying biological processes. However, existing models often struggle to integrate gene expression data with cellular spatial information effectively. Here we introduce SpatialForm...
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ISSN:2662-8457

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Haotian CuiChloe WangHassaan MaanKuan PangFengning Luo7
Nature Methods
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Generative pretrained models have achieved remarkable success in various domains such as language and computer vision. Specifically, the combination of large-scale diverse datasets and pretrained transformers has emerged as a promising approach for developing foundation models. Drawing parallels bet...
Computational modelsMachine learningSoftwareTranscriptomics
10.1038/S41592-024-02201-0
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