BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

187 related articles for article (PubMed ID: 38688285)

  • 21. Detection of Enriched T Cell Epitope Specificity in Full T Cell Receptor Sequence Repertoires.
    Gielis S; Moris P; Bittremieux W; De Neuter N; Ogunjimi B; Laukens K; Meysman P
    Front Immunol; 2019; 10():2820. PubMed ID: 31849987
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Attention-aware contrastive learning for predicting T cell receptor-antigen binding specificity.
    Fang Y; Liu X; Liu H
    Brief Bioinform; 2022 Nov; 23(6):. PubMed ID: 36094087
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Analysis of TCR β CDR3 sequencing data for tracking anti-tumor immunity.
    Zhang J; Ji Z; Smith KN
    Methods Enzymol; 2019; 629():443-464. PubMed ID: 31727253
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Mapping the functional landscape of T cell receptor repertoires by single-T cell transcriptomics.
    Zhang Z; Xiong D; Wang X; Liu H; Wang T
    Nat Methods; 2021 Jan; 18(1):92-99. PubMed ID: 33408405
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Analysis of T-Cell Receptor Repertoire in Transplantation: Fingerprint of T Cell-mediated Alloresponse.
    Tian G; Li M; Lv G
    Front Immunol; 2021; 12():778559. PubMed ID: 35095851
    [TBL] [Abstract][Full Text] [Related]  

  • 26. scRNA+TCR+BCR-seq revealed the proportions and gene expression patterns of dual receptor T and B lymphocytes in NPC and NLH.
    Yao Y; Wang H; Xu Y; Zhang L; Liu R
    Biochem Biophys Res Commun; 2024 May; 709():149820. PubMed ID: 38547605
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Recovery and analysis of transcriptome subsets from pooled single-cell RNA-seq libraries.
    Riemondy KA; Ransom M; Alderman C; Gillen AE; Fu R; Finlay-Schultz J; Kirkpatrick GD; Di Paola J; Kabos P; Sartorius CA; Hesselberth JR
    Nucleic Acids Res; 2019 Feb; 47(4):e20. PubMed ID: 30496484
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Visual Genomics Analysis Studio as a Tool to Analyze Multiomic Data.
    Hertzman RJ; Deshpande P; Leary S; Li Y; Ram R; Chopra A; Cooper D; Watson M; Palubinsky AM; Mallal S; Gibson A; Phillips EJ
    Front Genet; 2021; 12():642012. PubMed ID: 34220932
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Deep learning tackles single-cell analysis-a survey of deep learning for scRNA-seq analysis.
    Flores M; Liu Z; Zhang T; Hasib MM; Chiu YC; Ye Z; Paniagua K; Jo S; Zhang J; Gao SJ; Jin YF; Chen Y; Huang Y
    Brief Bioinform; 2022 Jan; 23(1):. PubMed ID: 34929734
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Comprehensive Integration of Single-Cell Data.
    Stuart T; Butler A; Hoffman P; Hafemeister C; Papalexi E; Mauck WM; Hao Y; Stoeckius M; Smibert P; Satija R
    Cell; 2019 Jun; 177(7):1888-1902.e21. PubMed ID: 31178118
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Single Cell Multiomic Approaches to Disentangle T Cell Heterogeneity.
    Abondio P; De Intinis C; da Silva Gonçalves Vianez Júnior JL; Pace L
    Immunol Lett; 2022 Jun; 246():37-51. PubMed ID: 35577000
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Efficient integration of heterogeneous single-cell transcriptomes using Scanorama.
    Hie B; Bryson B; Berger B
    Nat Biotechnol; 2019 Jun; 37(6):685-691. PubMed ID: 31061482
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Machine learning integrative approaches to advance computational immunology.
    Curion F; Theis FJ
    Genome Med; 2024 Jun; 16(1):80. PubMed ID: 38862979
    [TBL] [Abstract][Full Text] [Related]  

  • 34. LRT: Integrative analysis of scRNA-seq and scTCR-seq data to investigate clonal differentiation heterogeneity.
    Xie J; Jeon H; Xin G; Ma Q; Chung D
    PLoS Comput Biol; 2023 Jul; 19(7):e1011300. PubMed ID: 37428794
    [TBL] [Abstract][Full Text] [Related]  

  • 35. 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]  

  • 36. Latent cellular analysis robustly reveals subtle diversity in large-scale single-cell RNA-seq data.
    Cheng C; Easton J; Rosencrance C; Li Y; Ju B; Williams J; Mulder HL; Pang Y; Chen W; Chen X
    Nucleic Acids Res; 2019 Dec; 47(22):e143. PubMed ID: 31566233
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Contrastive self-supervised clustering of scRNA-seq data.
    Ciortan M; Defrance M
    BMC Bioinformatics; 2021 May; 22(1):280. PubMed ID: 34044773
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Single-Cell Analysis and Tracking of Antigen-Specific T Cells: Integrating Paired Chain AIRR-Seq and Transcriptome Sequencing: A Method by the AIRR Community.
    Gupta N; Lindeman I; Reinhardt S; Mariotti-Ferrandiz E; Mujangi-Ebeka K; Martins-Taylor K; Eugster A
    Methods Mol Biol; 2022; 2453():379-421. PubMed ID: 35622336
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Designing meaningful continuous representations of T cell receptor sequences with deep generative models.
    Leary AY; Scott D; Gupta NT; Waite JC; Skokos D; Atwal GS; Hawkins PG
    Nat Commun; 2024 May; 15(1):4271. PubMed ID: 38769289
    [TBL] [Abstract][Full Text] [Related]  

  • 40. 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]  

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