BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

484 related articles for article (PubMed ID: 34289014)

  • 21. scDCCA: deep contrastive clustering for single-cell RNA-seq data based on auto-encoder network.
    Wang J; Xia J; Wang H; Su Y; Zheng CH
    Brief Bioinform; 2023 Jan; 24(1):. PubMed ID: 36631401
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Spectral clustering based on learning similarity matrix.
    Park S; Zhao H
    Bioinformatics; 2018 Jun; 34(12):2069-2076. PubMed ID: 29432517
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Transfer learning for clustering single-cell RNA-seq data crossing-species and batch, case on uterine fibroids.
    Wang YM; Sun Y; Wang B; Wu Z; He XY; Zhao Y
    Brief Bioinform; 2023 Nov; 25(1):. PubMed ID: 37991248
    [TBL] [Abstract][Full Text] [Related]  

  • 24. PARC: ultrafast and accurate clustering of phenotypic data of millions of single cells.
    Stassen SV; Siu DMD; Lee KCM; Ho JWK; So HKH; Tsia KK
    Bioinformatics; 2020 May; 36(9):2778-2786. PubMed ID: 31971583
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Denoising adaptive deep clustering with self-attention mechanism on single-cell sequencing data.
    Su Y; Lin R; Wang J; Tan D; Zheng C
    Brief Bioinform; 2023 Mar; 24(2):. PubMed ID: 36715275
    [TBL] [Abstract][Full Text] [Related]  

  • 26. scDAC: deep adaptive clustering of single-cell transcriptomic data with coupled autoencoder and Dirichlet process mixture model.
    An S; Shi J; Liu R; Chen Y; Wang J; Hu S; Xia X; Dong G; Bo X; He Z; Ying X
    Bioinformatics; 2024 Mar; 40(4):. PubMed ID: 38603616
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Random forest based similarity learning for single cell RNA sequencing data.
    Pouyan MB; Kostka D
    Bioinformatics; 2018 Jul; 34(13):i79-i88. PubMed ID: 29950006
    [TBL] [Abstract][Full Text] [Related]  

  • 28. CONICS integrates scRNA-seq with DNA sequencing to map gene expression to tumor sub-clones.
    Müller S; Cho A; Liu SJ; Lim DA; Diaz A
    Bioinformatics; 2018 Sep; 34(18):3217-3219. PubMed ID: 29897414
    [TBL] [Abstract][Full Text] [Related]  

  • 29. 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]  

  • 30. A clustering method for small scRNA-seq data based on subspace and weighted distance.
    Ning Z; Dai Z; Zhang H; Chen Y; Yuan Z
    PeerJ; 2023; 11():e14706. PubMed ID: 36710872
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Joint learning dimension reduction and clustering of single-cell RNA-sequencing data.
    Wu W; Ma X
    Bioinformatics; 2020 Jun; 36(12):3825-3832. PubMed ID: 32246821
    [TBL] [Abstract][Full Text] [Related]  

  • 32. 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]  

  • 33. scDSSC: Deep Sparse Subspace Clustering for scRNA-seq Data.
    Wang H; Zhao J; Zheng C; Su Y
    PLoS Comput Biol; 2022 Dec; 18(12):e1010772. PubMed ID: 36534702
    [TBL] [Abstract][Full Text] [Related]  

  • 34. CellVGAE: an unsupervised scRNA-seq analysis workflow with graph attention networks.
    Buterez D; Bica I; Tariq I; Andrés-Terré H; Liò P
    Bioinformatics; 2022 Feb; 38(5):1277-1286. PubMed ID: 34864884
    [TBL] [Abstract][Full Text] [Related]  

  • 35. scASGC: An adaptive simplified graph convolution model for clustering single-cell RNA-seq data.
    Wang S; Zhang Y; Zhang Y; Wu W; Ye L; Li Y; Su J; Pang S
    Comput Biol Med; 2023 Sep; 163():107152. PubMed ID: 37364529
    [TBL] [Abstract][Full Text] [Related]  

  • 36. ICARUS v3, a massively scalable web server for single-cell RNA-seq analysis of millions of cells.
    Jiang A; Snell RG; Lehnert K
    Bioinformatics; 2024 Mar; 40(4):. PubMed ID: 38539041
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Ultra-fast scalable estimation of single-cell differentiation potency from scRNA-Seq data.
    Teschendorff AE; Maity AK; Hu X; Weiyan C; Lechner M
    Bioinformatics; 2021 Jul; 37(11):1528-1534. PubMed ID: 33244588
    [TBL] [Abstract][Full Text] [Related]  

  • 38. 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]  

  • 39. SCMcluster: a high-precision cell clustering algorithm integrating marker gene set with single-cell RNA sequencing data.
    Wu H; Zhou H; Zhou B; Wang M
    Brief Funct Genomics; 2023 Jul; 22(4):329-340. PubMed ID: 36848584
    [TBL] [Abstract][Full Text] [Related]  

  • 40. CASCC: a co-expression-assisted single-cell RNA-seq data clustering method.
    Cai L; Anastassiou D
    Bioinformatics; 2024 May; 40(5):. PubMed ID: 38662553
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 25.