236 related articles for article (PubMed ID: 36387277)
21. A Review of Integrative Imputation for Multi-Omics Datasets.
Song M; Greenbaum J; Luttrell J; Zhou W; Wu C; Shen H; Gong P; Zhang C; Deng HW
Front Genet; 2020; 11():570255. PubMed ID: 33193667
[TBL] [Abstract][Full Text] [Related]
22. Robust probabilistic modeling for single-cell multimodal mosaic integration and imputation via scVAEIT.
Du JH; Cai Z; Roeder K
Proc Natl Acad Sci U S A; 2022 Dec; 119(49):e2214414119. PubMed ID: 36459654
[TBL] [Abstract][Full Text] [Related]
23. Integrate multi-omics data with biological interaction networks using Multi-view Factorization AutoEncoder (MAE).
Ma T; Zhang A
BMC Genomics; 2019 Dec; 20(Suppl 11):944. PubMed ID: 31856727
[TBL] [Abstract][Full Text] [Related]
24. DeFusion: a denoised network regularization framework for multi-omics integration.
Wang W; Zhang X; Dai DQ
Brief Bioinform; 2021 Sep; 22(5):. PubMed ID: 33822879
[TBL] [Abstract][Full Text] [Related]
25. Integration strategies of multi-omics data for machine learning analysis.
Picard M; Scott-Boyer MP; Bodein A; Périn O; Droit A
Comput Struct Biotechnol J; 2021; 19():3735-3746. PubMed ID: 34285775
[TBL] [Abstract][Full Text] [Related]
26. scMCs: a framework for single-cell multi-omics data integration and multiple clusterings.
Ren L; Wang J; Li Z; Li Q; Yu G
Bioinformatics; 2023 Apr; 39(4):. PubMed ID: 36929930
[TBL] [Abstract][Full Text] [Related]
27. Computational strategies for single-cell multi-omics integration.
Adossa N; Khan S; Rytkönen KT; Elo LL
Comput Struct Biotechnol J; 2021; 19():2588-2596. PubMed ID: 34025945
[TBL] [Abstract][Full Text] [Related]
28. Deep learning based feature-level integration of multi-omics data for breast cancer patients survival analysis.
Tong L; Mitchel J; Chatlin K; Wang MD
BMC Med Inform Decis Mak; 2020 Sep; 20(1):225. PubMed ID: 32933515
[TBL] [Abstract][Full Text] [Related]
29. Missing data in multi-omics integration: Recent advances through artificial intelligence.
Flores JE; Claborne DM; Weller ZD; Webb-Robertson BM; Waters KM; Bramer LM
Front Artif Intell; 2023; 6():1098308. PubMed ID: 36844425
[TBL] [Abstract][Full Text] [Related]
30. Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases.
Sun YV; Hu YJ
Adv Genet; 2016; 93():147-90. PubMed ID: 26915271
[TBL] [Abstract][Full Text] [Related]
31. A comparative study of multi-omics integration tools for cancer driver gene identification and tumour subtyping.
Sathyanarayanan A; Gupta R; Thompson EW; Nyholt DR; Bauer DC; Nagaraj SH
Brief Bioinform; 2020 Dec; 21(6):1920-1936. PubMed ID: 31774481
[TBL] [Abstract][Full Text] [Related]
32. Unsupervised classification of multi-omics data during cardiac remodeling using deep learning.
Chung NC; Mirza B; Choi H; Wang J; Wang D; Ping P; Wang W
Methods; 2019 Aug; 166():66-73. PubMed ID: 30853547
[TBL] [Abstract][Full Text] [Related]
33. Ensemble learning models that predict surface protein abundance from single-cell multimodal omics data.
Xu F; Wang S; Dai X; Mundra PA; Zheng J
Methods; 2021 May; 189():65-73. PubMed ID: 33039573
[TBL] [Abstract][Full Text] [Related]
34. Liam tackles complex multimodal single-cell data integration challenges.
Rautenstrauch P; Ohler U
Nucleic Acids Res; 2024 Jun; ():. PubMed ID: 38842910
[TBL] [Abstract][Full Text] [Related]
35. Single-cell multi-omics topic embedding reveals cell-type-specific and COVID-19 severity-related immune signatures.
Zhou M; Zhang H; Bai Z; Mann-Krzisnik D; Wang F; Li Y
Cell Rep Methods; 2023 Aug; 3(8):100563. PubMed ID: 37671028
[TBL] [Abstract][Full Text] [Related]
36. Interpretable machine learning methods for predictions in systems biology from omics data.
Sidak D; Schwarzerová J; Weckwerth W; Waldherr S
Front Mol Biosci; 2022; 9():926623. PubMed ID: 36387282
[TBL] [Abstract][Full Text] [Related]
37. Interpretable generative deep learning: an illustration with single cell gene expression data.
Treppner M; Binder H; Hess M
Hum Genet; 2022 Sep; 141(9):1481-1498. PubMed ID: 34988661
[TBL] [Abstract][Full Text] [Related]
38. Discovery of drug-omics associations in type 2 diabetes with generative deep-learning models.
Allesøe RL; Lundgaard AT; Hernández Medina R; Aguayo-Orozco A; Johansen J; Nissen JN; Brorsson C; Mazzoni G; Niu L; Biel JH; Leal Rodríguez C; Brasas V; Webel H; Benros ME; Pedersen AG; Chmura PJ; Jacobsen UP; Mari A; Koivula R; Mahajan A; Vinuela A; Tajes JF; Sharma S; Haid M; Hong MG; Musholt PB; De Masi F; Vogt J; Pedersen HK; Gudmundsdottir V; Jones A; Kennedy G; Bell J; Thomas EL; Frost G; Thomsen H; Hansen E; Hansen TH; Vestergaard H; Muilwijk M; Blom MT; 't Hart LM; Pattou F; Raverdy V; Brage S; Kokkola T; Heggie A; McEvoy D; Mourby M; Kaye J; Hattersley A; McDonald T; Ridderstråle M; Walker M; Forgie I; Giordano GN; Pavo I; Ruetten H; Pedersen O; Hansen T; Dermitzakis E; Franks PW; Schwenk JM; Adamski J; McCarthy MI; Pearson E; Banasik K; Rasmussen S; Brunak S;
Nat Biotechnol; 2023 Mar; 41(3):399-408. PubMed ID: 36593394
[TBL] [Abstract][Full Text] [Related]
39. Metabolomics and Multi-Omics Integration: A Survey of Computational Methods and Resources.
Eicher T; Kinnebrew G; Patt A; Spencer K; Ying K; Ma Q; Machiraju R; Mathé AEA
Metabolites; 2020 May; 10(5):. PubMed ID: 32429287
[TBL] [Abstract][Full Text] [Related]
40. Multi-omics analysis in developmental bone biology.
Matsushita Y; Noguchi A; Ono W; Ono N
Jpn Dent Sci Rev; 2023 Dec; 59():412-420. PubMed ID: 38022387
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
