These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

265 related articles for article (PubMed ID: 33039573)

  • 21. Optimising protein detection with fixable custom oligo-labelled antibodies for single-cell multi-omics approaches.
    Kleino I; Nowlan K; Kotimaa J; Kekäläinen E
    Biotechnol J; 2022 Jun; 17(6):e2100213. PubMed ID: 35174641
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Semisupervised Generative Autoencoder for Single-Cell Data.
    Trong TN; Mehtonen J; González G; Kramer R; Hautamäki V; Heinäniemi M
    J Comput Biol; 2020 Aug; 27(8):1190-1203. PubMed ID: 31794242
    [No Abstract]   [Full Text] [Related]  

  • 23. Improved integration of single-cell transcriptome and surface protein expression by LinQ-View.
    Li L; Dugan HL; Stamper CT; Lan LY; Asby NW; Knight M; Stovicek O; Zheng NY; Madariaga ML; Shanmugarajah K; Jansen MO; Changrob S; Utset HA; Henry C; Nelson C; Jedrzejczak RP; Fremont DH; Joachimiak A; Krammer F; Huang J; Khan AA; Wilson PC
    Cell Rep Methods; 2021 Aug; 1(4):100056. PubMed ID: 35475142
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Efficient Generation of Paired Single-Cell Multiomics Profiles by Deep Learning.
    Lan M; Zhang S; Gao L
    Adv Sci (Weinh); 2023 Jul; 10(21):e2301169. PubMed ID: 37114830
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Deep learning in omics: a survey and guideline.
    Zhang Z; Zhao Y; Liao X; Shi W; Li K; Zou Q; Peng S
    Brief Funct Genomics; 2019 Feb; 18(1):41-57. PubMed ID: 30265280
    [TBL] [Abstract][Full Text] [Related]  

  • 26. scmFormer Integrates Large-Scale Single-Cell Proteomics and Transcriptomics Data by Multi-Task Transformer.
    Xu J; Huang DS; Zhang X
    Adv Sci (Weinh); 2024 May; 11(19):e2307835. PubMed ID: 38483032
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Integrating pathway knowledge with deep neural networks to reduce the dimensionality in single-cell RNA-seq data.
    Gundogdu P; Loucera C; Alamo-Alvarez I; Dopazo J; Nepomuceno I
    BioData Min; 2022 Jan; 15(1):1. PubMed ID: 34980200
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Clustering CITE-seq data with a canonical correlation-based deep learning method.
    Yuan M; Chen L; Deng M
    Front Genet; 2022; 13():977968. PubMed ID: 36072672
    [TBL] [Abstract][Full Text] [Related]  

  • 29. A machine learning approach for the identification of key markers involved in brain development from single-cell transcriptomic data.
    Hu Y; Hase T; Li HP; Prabhakar S; Kitano H; Ng SK; Ghosh S; Wee LJ
    BMC Genomics; 2016 Dec; 17(Suppl 13):1025. PubMed ID: 28155657
    [TBL] [Abstract][Full Text] [Related]  

  • 30. DeepHE: Accurately predicting human essential genes based on deep learning.
    Zhang X; Xiao W; Xiao W
    PLoS Comput Biol; 2020 Sep; 16(9):e1008229. PubMed ID: 32936825
    [TBL] [Abstract][Full Text] [Related]  

  • 31. deepMc: Deep Matrix Completion for Imputation of Single-Cell RNA-seq Data.
    Mongia A; Sengupta D; Majumdar A
    J Comput Biol; 2020 Jul; 27(7):1011-1019. PubMed ID: 31657645
    [TBL] [Abstract][Full Text] [Related]  

  • 32. DISC: a highly scalable and accurate inference of gene expression and structure for single-cell transcriptomes using semi-supervised deep learning.
    He Y; Yuan H; Wu C; Xie Z
    Genome Biol; 2020 Jul; 21(1):170. PubMed ID: 32650816
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Knowledge-primed neural networks enable biologically interpretable deep learning on single-cell sequencing data.
    Fortelny N; Bock C
    Genome Biol; 2020 Aug; 21(1):190. PubMed ID: 32746932
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Network-based drug sensitivity prediction.
    Ahmed KT; Park S; Jiang Q; Yeu Y; Hwang T; Zhang W
    BMC Med Genomics; 2020 Dec; 13(Suppl 11):193. PubMed ID: 33371891
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Ensemble dimensionality reduction and feature gene extraction for single-cell RNA-seq data.
    Sun X; Liu Y; An L
    Nat Commun; 2020 Nov; 11(1):5853. PubMed ID: 33203837
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Interpretable deep learning in single-cell omics.
    Wagle MM; Long S; Chen C; Liu C; Yang P
    Bioinformatics; 2024 Jun; 40(6):. PubMed ID: 38889275
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Biological and Medical Importance of Cellular Heterogeneity Deciphered by Single-Cell RNA Sequencing.
    Gupta RK; Kuznicki J
    Cells; 2020 Jul; 9(8):. PubMed ID: 32707839
    [TBL] [Abstract][Full Text] [Related]  

  • 38. A flexible network-based imputing-and-fusing approach towards the identification of cell types from single-cell RNA-seq data.
    Qi Y; Guo Y; Jiao H; Shang X
    BMC Bioinformatics; 2020 Jun; 21(1):240. PubMed ID: 32527285
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Potential applications of deep learning in single-cell RNA sequencing analysis for cell therapy and regenerative medicine.
    Yan R; Fan C; Yin Z; Wang T; Chen X
    Stem Cells; 2021 May; 39(5):511-521. PubMed ID: 33587792
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Single-cell multi-omics integration for unpaired data by a siamese network with graph-based contrastive loss.
    Liu C; Wang L; Liu Z
    BMC Bioinformatics; 2023 Jan; 24(1):5. PubMed ID: 36600199
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 14.