Assessing parameter efficient methods for pre-trained language model in annotating scRNA-seq data-Reference-Cited by-同舟云学术

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Assessing parameter efficient methods for pre-trained language model in annotating scRNA-seq data

Published:2024-08 Issue: Volume:228 Page:12-21
ISSN:1046-2023
Container-title:Methods
language:en
Short-container-title:Methods

Author:

Xia Yucheng,Liu Yuhang,Li Tianhao,He Sihan,Chang Hong,Wang Yaqing,Zhang Yongqing^ORCID,Ge Wenyi

Publisher

Elsevier BV

Reference45 articles.

1. Challenges in unsupervised clustering of single-cell rna-seq data;Kiselev;Nat. Rev. Genet.,2019

2. Comparative analysis of oncogenes identified by microarray and rna-sequencing as biomarkers for clinical prognosis;Liu;Biomark. Med.,2015

3. Systematic comparison of single-cell and single-nucleus rna-sequencing methods;Ding;Nat. Biotechnol.,2020

4. Narrowing the gap between in vitro and in vivo genetic profiles by deconvoluting toxicogenomic data in silico;Liu;Front. Pharmacol.,2020

5. Single-cell rna sequencing in cardiovascular development, disease and medicine;Paik;Nature Rev. Cardiol.,2020

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1. Advanced deep learning approaches enable high-throughput biological and biomedicine data analysis;Methods;2024-10

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