BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

175 related articles for article (PubMed ID: 29939207)

  • 1. A descriptive marker gene approach to single-cell pseudotime inference.
    Campbell KR; Yau C
    Bioinformatics; 2019 Jan; 35(1):28-35. PubMed ID: 29939207
    [TBL] [Abstract][Full Text] [Related]  

  • 2. psupertime: supervised pseudotime analysis for time-series single-cell RNA-seq data.
    Macnair W; Gupta R; Claassen M
    Bioinformatics; 2022 Jun; 38(Suppl 1):i290-i298. PubMed ID: 35758781
    [TBL] [Abstract][Full Text] [Related]  

  • 3. scShaper: an ensemble method for fast and accurate linear trajectory inference from single-cell RNA-seq data.
    Smolander J; Junttila S; Venäläinen MS; Elo LL
    Bioinformatics; 2022 Feb; 38(5):1328-1335. PubMed ID: 34888622
    [TBL] [Abstract][Full Text] [Related]  

  • 4. switchde: inference of switch-like differential expression along single-cell trajectories.
    Campbell KR; Yau C
    Bioinformatics; 2017 Apr; 33(8):1241-1242. PubMed ID: 28011787
    [TBL] [Abstract][Full Text] [Related]  

  • 5. HopLand: single-cell pseudotime recovery using continuous Hopfield network-based modeling of Waddington's epigenetic landscape.
    Guo J; Zheng J
    Bioinformatics; 2017 Jul; 33(14):i102-i109. PubMed ID: 28881967
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A robust and accurate single-cell data trajectory inference method using ensemble pseudotime.
    Zhang Y; Tran D; Nguyen T; Dascalu SM; Harris FC
    BMC Bioinformatics; 2023 Feb; 24(1):55. PubMed ID: 36803767
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Single-cell generalized trend model (scGTM): a flexible and interpretable model of gene expression trend along cell pseudotime.
    Cui EH; Song D; Wong WK; Li JJ
    Bioinformatics; 2022 Aug; 38(16):3927-3934. PubMed ID: 35758616
    [TBL] [Abstract][Full Text] [Related]  

  • 8. PseudoGA: cell pseudotime reconstruction based on genetic algorithm.
    Mondal PK; Saha US; Mukhopadhyay I
    Nucleic Acids Res; 2021 Aug; 49(14):7909-7924. PubMed ID: 34244782
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Network inference with Granger causality ensembles on single-cell transcriptomics.
    Deshpande A; Chu LF; Stewart R; Gitter A
    Cell Rep; 2022 Feb; 38(6):110333. PubMed ID: 35139376
    [TBL] [Abstract][Full Text] [Related]  

  • 10. GPseudoRank: a permutation sampler for single cell orderings.
    Strauß ME; Reid JE; Wernisch L
    Bioinformatics; 2019 Feb; 35(4):611-618. PubMed ID: 30052778
    [TBL] [Abstract][Full Text] [Related]  

  • 11. scEpath: energy landscape-based inference of transition probabilities and cellular trajectories from single-cell transcriptomic data.
    Jin S; MacLean AL; Peng T; Nie Q
    Bioinformatics; 2018 Jun; 34(12):2077-2086. PubMed ID: 29415263
    [TBL] [Abstract][Full Text] [Related]  

  • 12. GPseudoClust: deconvolution of shared pseudo-profiles at single-cell resolution.
    Strauss ME; Kirk PDW; Reid JE; Wernisch L
    Bioinformatics; 2020 Mar; 36(5):1484-1491. PubMed ID: 31608923
    [TBL] [Abstract][Full Text] [Related]  

  • 13. GrandPrix: scaling up the Bayesian GPLVM for single-cell data.
    Ahmed S; Rattray M; Boukouvalas A
    Bioinformatics; 2019 Jan; 35(1):47-54. PubMed ID: 30561544
    [TBL] [Abstract][Full Text] [Related]  

  • 14. DELVE: feature selection for preserving biological trajectories in single-cell data.
    Ranek JS; Stallaert W; Milner JJ; Redick M; Wolff SC; Beltran AS; Stanley N; Purvis JE
    Nat Commun; 2024 Mar; 15(1):2765. PubMed ID: 38553455
    [TBL] [Abstract][Full Text] [Related]  

  • 15. PseudotimeDE: inference of differential gene expression along cell pseudotime with well-calibrated p-values from single-cell RNA sequencing data.
    Song D; Li JJ
    Genome Biol; 2021 Apr; 22(1):124. PubMed ID: 33926517
    [TBL] [Abstract][Full Text] [Related]  

  • 16. LEAP: constructing gene co-expression networks for single-cell RNA-sequencing data using pseudotime ordering.
    Specht AT; Li J
    Bioinformatics; 2017 Mar; 33(5):764-766. PubMed ID: 27993778
    [TBL] [Abstract][Full Text] [Related]  

  • 17. BLTSA: pseudotime prediction for single cells by branched local tangent space alignment.
    Li L; Zhao Y; Li H; Zhang S
    Bioinformatics; 2023 Feb; 39(2):. PubMed ID: 36692140
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Pseudotime Reconstruction Using TSCAN.
    Ji Z; Ji H
    Methods Mol Biol; 2019; 1935():115-124. PubMed ID: 30758823
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Slingshot: cell lineage and pseudotime inference for single-cell transcriptomics.
    Street K; Risso D; Fletcher RB; Das D; Ngai J; Yosef N; Purdom E; Dudoit S
    BMC Genomics; 2018 Jun; 19(1):477. PubMed ID: 29914354
    [TBL] [Abstract][Full Text] [Related]  

  • 20. scHiCPTR: unsupervised pseudotime inference through dual graph refinement for single-cell Hi-C data.
    Lyu H; Liu E; Wu Z; Li Y; Liu Y; Yin X
    Bioinformatics; 2022 Nov; 38(23):5151-5159. PubMed ID: 36205615
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.