Generative pretraining from large-scale transcriptomes for single-cell deciphering-Reference-Cited by-同舟云学术

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Generative pretraining from large-scale transcriptomes for single-cell deciphering

Published:2023-05 Issue:5 Volume:26 Page:106536
ISSN:2589-0042
Container-title:iScience
language:en
Short-container-title:iScience

Author:

Shen Hongru,Liu Jilei,Hu Jiani,Shen Xilin,Zhang Chao,Wu Dan,Feng Mengyao,Yang Meng,Li Yang,Yang Yichen,Wang Wei,Zhang Qiang,Yang Jilong,Chen Kexin,Li Xiangchun

Publisher

Elsevier BV

Subject

Multidisciplinary

Reference59 articles.

1. The human cell atlas;Regev;Elife,2017

2. Expression Atlas update: from tissues to single cells;Papatheodorou;Nucleic Acids Res.,2020

3. A single-cell atlas of the peripheral immune response in patients with severe COVID-19;Wilk;Nat. Med.,2020

4. Single-cell transcriptomics of 20 mouse organs creates a Tabula Muris;Nature,2018

5. Mapping the mouse cell atlas by microwell-seq;Han;Cell,2018

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1. Profiling cell identity and tissue architecture with single-cell and spatial transcriptomics;Nature Reviews Molecular Cell Biology;2024-08-21

2. Transformers in single-cell omics: a review and new perspectives;Nature Methods;2024-08

3. Robust evaluation of deep learning-based representation methods for survival and gene essentiality prediction on bulk RNA-seq data;Scientific Reports;2024-07-24

4. Perspectives on benchmarking foundation models for network biology;Quantitative Biology;2024-07-11

5. CellFM: a large-scale foundation model pre-trained on transcriptomics of 100 million human cells;2024-06-06

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