356 related articles for article (PubMed ID: 34791014)
21. Towards artificial intelligence to multi-omics characterization of tumor heterogeneity in esophageal cancer.
Li J; Li L; You P; Wei Y; Xu B
Semin Cancer Biol; 2023 Jun; 91():35-49. PubMed ID: 36868394
[TBL] [Abstract][Full Text] [Related]
22. Applications of multi-omics analysis in human diseases.
Chen C; Wang J; Pan D; Wang X; Xu Y; Yan J; Wang L; Yang X; Yang M; Liu GP
MedComm (2020); 2023 Aug; 4(4):e315. PubMed ID: 37533767
[TBL] [Abstract][Full Text] [Related]
23. Machine learning and systems genomics approaches for multi-omics data.
Lin E; Lane HY
Biomark Res; 2017; 5():2. PubMed ID: 28127429
[TBL] [Abstract][Full Text] [Related]
24. 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]
25. Deep learning assisted multi-omics integration for survival and drug-response prediction in breast cancer.
Malik V; Kalakoti Y; Sundar D
BMC Genomics; 2021 Mar; 22(1):214. PubMed ID: 33761889
[TBL] [Abstract][Full Text] [Related]
26. Computational frameworks integrating deep learning and statistical models in mining multimodal omics data.
Lac L; Leung CK; Hu P
J Biomed Inform; 2024 Apr; 152():104629. PubMed ID: 38552994
[TBL] [Abstract][Full Text] [Related]
27. Multi-omics data integration methods and their applications in psychiatric disorders.
Sathyanarayanan A; Mueller TT; Ali Moni M; Schueler K; ; Baune BT; Lio P; Mehta D; Baune BT; Dierssen M; Ebert B; Fabbri C; Fusar-Poli P; Gennarelli M; Harmer C; Howes OD; Janzing JGE; Lio P; Maron E; Mehta D; Minelli A; Nonell L; Pisanu C; Potier MC; Rybakowski F; Serretti A; Squassina A; Stacey D; van Westrhenen R; Xicota L
Eur Neuropsychopharmacol; 2023 Apr; 69():26-46. PubMed ID: 36706689
[TBL] [Abstract][Full Text] [Related]
28. Capturing the latent space of an Autoencoder for multi-omics integration and cancer subtyping.
Madhumita ; Paul S
Comput Biol Med; 2022 Sep; 148():105832. PubMed ID: 35834966
[TBL] [Abstract][Full Text] [Related]
29. Integrative multi-omics and systems bioinformatics in translational neuroscience: A data mining perspective.
O'Connor LM; O'Connor BA; Lim SB; Zeng J; Lo CH
J Pharm Anal; 2023 Aug; 13(8):836-850. PubMed ID: 37719197
[TBL] [Abstract][Full Text] [Related]
30. DNNGP, a deep neural network-based method for genomic prediction using multi-omics data in plants.
Wang K; Abid MA; Rasheed A; Crossa J; Hearne S; Li H
Mol Plant; 2023 Jan; 16(1):279-293. PubMed ID: 36366781
[TBL] [Abstract][Full Text] [Related]
31. Integrating multi-omics data through deep learning for accurate cancer prognosis prediction.
Chai H; Zhou X; Zhang Z; Rao J; Zhao H; Yang Y
Comput Biol Med; 2021 Jul; 134():104481. PubMed ID: 33989895
[TBL] [Abstract][Full Text] [Related]
32. Knowledge-guided learning methods for integrative analysis of multi-omics data.
Li W; Ballard J; Zhao Y; Long Q
Comput Struct Biotechnol J; 2024 Dec; 23():1945-1950. PubMed ID: 38736693
[TBL] [Abstract][Full Text] [Related]
33. A scoping review on deep learning for next-generation RNA-Seq. data analysis.
Pandey D; Onkara Perumal P
Funct Integr Genomics; 2023 Apr; 23(2):134. PubMed ID: 37084004
[TBL] [Abstract][Full Text] [Related]
34. Multi-omics integration in biomedical research - A metabolomics-centric review.
Wörheide MA; Krumsiek J; Kastenmüller G; Arnold M
Anal Chim Acta; 2021 Jan; 1141():144-162. PubMed ID: 33248648
[TBL] [Abstract][Full Text] [Related]
35. An integrative imputation method based on multi-omics datasets.
Lin D; Zhang J; Li J; Xu C; Deng HW; Wang YP
BMC Bioinformatics; 2016 Jun; 17():247. PubMed ID: 27329642
[TBL] [Abstract][Full Text] [Related]
36. Deep Learning-Based Multi-Omics Integration Robustly Predicts Survival in Liver Cancer.
Chaudhary K; Poirion OB; Lu L; Garmire LX
Clin Cancer Res; 2018 Mar; 24(6):1248-1259. PubMed ID: 28982688
[TBL] [Abstract][Full Text] [Related]
37. A denoised multi-omics integration framework for cancer subtype classification and survival prediction.
Pang J; Liang B; Ding R; Yan Q; Chen R; Xu J
Brief Bioinform; 2023 Sep; 24(5):. PubMed ID: 37594302
[TBL] [Abstract][Full Text] [Related]
38. Predicting Deep Learning Based Multi-Omics Parallel Integration Survival Subtypes in Lung Cancer Using Reverse Phase Protein Array Data.
Takahashi S; Asada K; Takasawa K; Shimoyama R; Sakai A; Bolatkan A; Shinkai N; Kobayashi K; Komatsu M; Kaneko S; Sese J; Hamamoto R
Biomolecules; 2020 Oct; 10(10):. PubMed ID: 33086649
[TBL] [Abstract][Full Text] [Related]
39. Integrating multi-omics data by learning modality invariant representations for improved prediction of overall survival of cancer.
Tong L; Wu H; Wang MD
Methods; 2021 May; 189():74-85. PubMed ID: 32763377
[TBL] [Abstract][Full Text] [Related]
40. An overview of technologies for MS-based proteomics-centric multi-omics.
Rajczewski AT; Jagtap PD; Griffin TJ
Expert Rev Proteomics; 2022 Mar; 19(3):165-181. PubMed ID: 35466851
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
