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 *

192 related articles for article (PubMed ID: 35963997)

  • 41. Model-based deep embedding for constrained clustering analysis of single cell RNA-seq data.
    Tian T; Zhang J; Lin X; Wei Z; Hakonarson H
    Nat Commun; 2021 Mar; 12(1):1873. PubMed ID: 33767149
    [TBL] [Abstract][Full Text] [Related]  

  • 42. AutoImpute: Autoencoder based imputation of single-cell RNA-seq data.
    Talwar D; Mongia A; Sengupta D; Majumdar A
    Sci Rep; 2018 Nov; 8(1):16329. PubMed ID: 30397240
    [TBL] [Abstract][Full Text] [Related]  

  • 43. jSRC: a flexible and accurate joint learning algorithm for clustering of single-cell RNA-sequencing data.
    Wu W; Liu Z; Ma X
    Brief Bioinform; 2021 Sep; 22(5):. PubMed ID: 33535230
    [TBL] [Abstract][Full Text] [Related]  

  • 44. Parameter tuning is a key part of dimensionality reduction via deep variational autoencoders for single cell RNA transcriptomics.
    Hu Q; Greene CS
    Pac Symp Biocomput; 2019; 24():362-373. PubMed ID: 30963075
    [TBL] [Abstract][Full Text] [Related]  

  • 45. One Cell At a Time (OCAT): a unified framework to integrate and analyze single-cell RNA-seq data.
    Wang CX; Zhang L; Wang B
    Genome Biol; 2022 Apr; 23(1):102. PubMed ID: 35443717
    [TBL] [Abstract][Full Text] [Related]  

  • 46. Topological and geometric analysis of cell states in single-cell transcriptomic data.
    Huynh T; Cang Z
    Brief Bioinform; 2024 Mar; 25(3):. PubMed ID: 38632952
    [TBL] [Abstract][Full Text] [Related]  

  • 47. Multi-View Clustering With Graph Learning for scRNA-Seq Data.
    Wu W; Zhang W; Hou W; Ma X
    IEEE/ACM Trans Comput Biol Bioinform; 2023; 20(6):3535-3546. PubMed ID: 37486829
    [TBL] [Abstract][Full Text] [Related]  

  • 48. scSemiAAE: a semi-supervised clustering model for single-cell RNA-seq data.
    Wang Z; Wang H; Zhao J; Zheng C
    BMC Bioinformatics; 2023 May; 24(1):217. PubMed ID: 37237310
    [TBL] [Abstract][Full Text] [Related]  

  • 49. On the use of QDE-SVM for gene feature selection and cell type classification from scRNA-seq data.
    Ng GYL; Tan SC; Ong CS
    PLoS One; 2023; 18(10):e0292961. PubMed ID: 37856458
    [TBL] [Abstract][Full Text] [Related]  

  • 50. Comparison of scRNA-seq data analysis method combinations.
    Xu L; Xue T; Ding W; Shen L
    Brief Funct Genomics; 2022 Nov; 21(6):433-440. PubMed ID: 36124658
    [TBL] [Abstract][Full Text] [Related]  

  • 51. Application of Deep Learning on Single-cell RNA Sequencing Data Analysis: A Review.
    Brendel M; Su C; Bai Z; Zhang H; Elemento O; Wang F
    Genomics Proteomics Bioinformatics; 2022 Oct; 20(5):814-835. PubMed ID: 36528240
    [TBL] [Abstract][Full Text] [Related]  

  • 52. scMAGS: Marker gene selection from scRNA-seq data for spatial transcriptomics studies.
    Baran Y; Doğan B
    Comput Biol Med; 2023 Mar; 155():106634. PubMed ID: 36774895
    [TBL] [Abstract][Full Text] [Related]  

  • 53. Bubble: a fast single-cell RNA-seq imputation using an autoencoder constrained by bulk RNA-seq data.
    Chen S; Yan X; Zheng R; Li M
    Brief Bioinform; 2023 Jan; 24(1):. PubMed ID: 36567258
    [TBL] [Abstract][Full Text] [Related]  

  • 54. Single Cell Self-Paced Clustering with Transcriptome Sequencing Data.
    Zhao P; Xu Z; Chen J; Ren Y; King I
    Int J Mol Sci; 2022 Mar; 23(7):. PubMed ID: 35409258
    [TBL] [Abstract][Full Text] [Related]  

  • 55. Benchmarking imputation methods for network inference using a novel method of synthetic scRNA-seq data generation.
    Lasri A; Shahrezaei V; Sturrock M
    BMC Bioinformatics; 2022 Jun; 23(1):236. PubMed ID: 35715748
    [TBL] [Abstract][Full Text] [Related]  

  • 56. scGGAN: single-cell RNA-seq imputation by graph-based generative adversarial network.
    Huang Z; Wang J; Lu X; Mohd Zain A; Yu G
    Brief Bioinform; 2023 Mar; 24(2):. PubMed ID: 36733262
    [TBL] [Abstract][Full Text] [Related]  

  • 57. VPAC: Variational projection for accurate clustering of single-cell transcriptomic data.
    Chen S; Hua K; Cui H; Jiang R
    BMC Bioinformatics; 2019 May; 20(Suppl 7):0. PubMed ID: 31074382
    [TBL] [Abstract][Full Text] [Related]  

  • 58. An Informative Approach to Single-Cell Sequencing Analysis.
    Kashima Y; Suzuki A; Suzuki Y
    Adv Exp Med Biol; 2019; 1129():81-96. PubMed ID: 30968362
    [TBL] [Abstract][Full Text] [Related]  

  • 59. SPANN: annotating single-cell resolution spatial transcriptome data with scRNA-seq data.
    Yuan M; Wan H; Wang Z; Guo Q; Deng M
    Brief Bioinform; 2024 Jan; 25(2):. PubMed ID: 38279647
    [TBL] [Abstract][Full Text] [Related]  

  • 60. SSNMDI: a novel joint learning model of semi-supervised non-negative matrix factorization and data imputation for clustering of single-cell RNA-seq data.
    Qiu Y; Yan C; Zhao P; Zou Q
    Brief Bioinform; 2023 May; 24(3):. PubMed ID: 37122068
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 10.