BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

124 related articles for article (PubMed ID: 38940174)

  • 1. AttentionPert: accurately modeling multiplexed genetic perturbations with multi-scale effects.
    Bai D; Ellington CN; Mo S; Song L; Xing EP
    Bioinformatics; 2024 Jun; 40(Supplement_1):i453-i461. PubMed ID: 38940174
    [TBL] [Abstract][Full Text] [Related]  

  • 2. scPRAM accurately predicts single-cell gene expression perturbation response based on attention mechanism.
    Jiang Q; Chen S; Chen X; Jiang R
    Bioinformatics; 2024 May; 40(5):. PubMed ID: 38625746
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Predicting single-cell cellular responses to perturbations using cycle consistency learning.
    Huang W; Liu H
    Bioinformatics; 2024 Jun; 40(Supplement_1):i462-i470. PubMed ID: 38940153
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Learning gene networks under SNP perturbations using eQTL datasets.
    Zhang L; Kim S
    PLoS Comput Biol; 2014 Feb; 10(2):e1003420. PubMed ID: 24586125
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Genetic Neural Networks: an artificial neural network architecture for capturing gene expression relationships.
    Eetemadi A; Tagkopoulos I
    Bioinformatics; 2019 Jul; 35(13):2226-2234. PubMed ID: 30452523
    [TBL] [Abstract][Full Text] [Related]  

  • 6. CancerOmicsNet: a multi-omics network-based approach to anti-cancer drug profiling.
    Pu L; Singha M; Ramanujam J; Brylinski M
    Oncotarget; 2022; 13():695-706. PubMed ID: 35601606
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Ensemble machine learning model trained on a new synthesized dataset generalizes well for stress prediction using wearable devices.
    Vos G; Trinh K; Sarnyai Z; Rahimi Azghadi M
    J Biomed Inform; 2023 Dec; 148():104556. PubMed ID: 38048895
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Predicting dynamic signaling network response under unseen perturbations.
    Zhu F; Guan Y
    Bioinformatics; 2014 Oct; 30(19):2772-8. PubMed ID: 24919880
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Predicting transcriptional outcomes of novel multigene perturbations with GEARS.
    Roohani Y; Huang K; Leskovec J
    Nat Biotechnol; 2024 Jun; 42(6):927-935. PubMed ID: 37592036
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Predicting cellular responses to complex perturbations in high-throughput screens.
    Lotfollahi M; Klimovskaia Susmelj A; De Donno C; Hetzel L; Ji Y; Ibarra IL; Srivatsan SR; Naghipourfar M; Daza RM; Martin B; Shendure J; McFaline-Figueroa JL; Boyeau P; Wolf FA; Yakubova N; Günnemann S; Trapnell C; Lopez-Paz D; Theis FJ
    Mol Syst Biol; 2023 Jun; 19(6):e11517. PubMed ID: 37154091
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Accurately modeling biased random walks on weighted networks using node2vec.
    Liu R; Hirn M; Krishnan A
    Bioinformatics; 2023 Jan; 39(1):. PubMed ID: 36688699
    [TBL] [Abstract][Full Text] [Related]  

  • 12. DeltaNeTS+: elucidating the mechanism of drugs and diseases using gene expression and transcriptional regulatory networks.
    Noh H; Hua Z; Chrysinas P; Shoemaker JE; Gunawan R
    BMC Bioinformatics; 2021 Mar; 22(1):108. PubMed ID: 33663384
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Predicting gene targets of perturbations via network-based filtering of mRNA expression compendia.
    Cosgrove EJ; Zhou Y; Gardner TS; Kolaczyk ED
    Bioinformatics; 2008 Nov; 24(21):2482-90. PubMed ID: 18779235
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Predicting mechanism of action of cellular perturbations with pathway activity signatures.
    Ren Y; Sivaganesan S; Clark NA; Zhang L; Biesiada J; Niu W; Plas DR; Medvedovic M
    Bioinformatics; 2020 Sep; 36(18):4781-4788. PubMed ID: 32653926
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Topological benchmarking of algorithms to infer gene regulatory networks from single-cell RNA-seq data.
    Stock M; Popp N; Fiorentino J; Scialdone A
    Bioinformatics; 2024 May; 40(5):. PubMed ID: 38627250
    [TBL] [Abstract][Full Text] [Related]  

  • 16. TITER: predicting translation initiation sites by deep learning.
    Zhang S; Hu H; Jiang T; Zhang L; Zeng J
    Bioinformatics; 2017 Jul; 33(14):i234-i242. PubMed ID: 28881981
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Transfer learning of condition-specific perturbation in gene interactions improves drug response prediction.
    Bang D; Koo B; Kim S
    Bioinformatics; 2024 Jun; 40(Supplement_1):i130-i139. PubMed ID: 38940127
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Differential expression analysis with global network adjustment.
    Gelfond JA; Ibrahim JG; Gupta M; Chen MH; Cody JD
    BMC Bioinformatics; 2013 Aug; 14():258. PubMed ID: 23968143
    [TBL] [Abstract][Full Text] [Related]  

  • 19. OutPredict: multiple datasets can improve prediction of expression and inference of causality.
    Cirrone J; Brooks MD; Bonneau R; Coruzzi GM; Shasha DE
    Sci Rep; 2020 Apr; 10(1):6804. PubMed ID: 32321967
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Learning signaling networks from combinatorial perturbations by exploiting siRNA off-target effects.
    Tiuryn J; Szczurek E
    Bioinformatics; 2019 Jul; 35(14):i605-i614. PubMed ID: 31510678
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.