233 related articles for article (PubMed ID: 32601549)
21. Multi-omics facilitated variable selection in Cox-regression model for cancer prognosis prediction.
Liu C; Wang X; Genchev GZ; Lu H
Methods; 2017 Jul; 124():100-107. PubMed ID: 28627406
[TBL] [Abstract][Full Text] [Related]
22. Comparative Evaluation of Machine Learning Models for Subtyping Triple-Negative Breast Cancer: A Deep Learning-Based Multi-Omics Data Integration Approach.
Yang S; Wang Z; Wang C; Li C; Wang B
J Cancer; 2024; 15(12):3943-3957. PubMed ID: 38911381
[No Abstract] [Full Text] [Related]
23. Survival prediction in patients with colon adenocarcinoma via multi-omics data integration using a deep learning algorithm.
Lv J; Wang J; Shang X; Liu F; Guo S
Biosci Rep; 2020 Dec; 40(12):. PubMed ID: 33258470
[TBL] [Abstract][Full Text] [Related]
24. Supervised graph contrastive learning for cancer subtype identification through multi-omics data integration.
Chen F; Peng W; Dai W; Wei S; Fu X; Liu L; Liu L
Health Inf Sci Syst; 2024 Dec; 12(1):12. PubMed ID: 38404715
[TBL] [Abstract][Full Text] [Related]
25. 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]
26. A hierarchical integration deep flexible neural forest framework for cancer subtype classification by integrating multi-omics data.
Xu J; Wu P; Chen Y; Meng Q; Dawood H; Dawood H
BMC Bioinformatics; 2019 Oct; 20(1):527. PubMed ID: 31660856
[TBL] [Abstract][Full Text] [Related]
27. Identification of cancer risk groups through multi-omics integration using autoencoder and tensor analysis.
Braytee A; He S; Tang S; Sun Y; Jiang X; Yu X; Khatri I; Chaturvedi K; Prasad M; Anaissi A
Sci Rep; 2024 May; 14(1):11263. PubMed ID: 38760420
[TBL] [Abstract][Full Text] [Related]
28. Histopathological Images and Multi-Omics Integration Predict Molecular Characteristics and Survival in Lung Adenocarcinoma.
Chen L; Zeng H; Xiang Y; Huang Y; Luo Y; Ma X
Front Cell Dev Biol; 2021; 9():720110. PubMed ID: 34708036
[TBL] [Abstract][Full Text] [Related]
29. Evaluating DNA Methylation, Gene Expression, Somatic Mutation, and Their Combinations in Inferring Tumor Tissue-of-Origin.
Liu H; Qiu C; Wang B; Bing P; Tian G; Zhang X; Ma J; He B; Yang J
Front Cell Dev Biol; 2021; 9():619330. PubMed ID: 34012960
[TBL] [Abstract][Full Text] [Related]
30. Incorporating inter-relationships between different levels of genomic data into cancer clinical outcome prediction.
Kim D; Shin H; Sohn KA; Verma A; Ritchie MD; Kim JH
Methods; 2014 Jun; 67(3):344-53. PubMed ID: 24561168
[TBL] [Abstract][Full Text] [Related]
31. BRCA-Pathway: a structural integration and visualization system of TCGA breast cancer data on KEGG pathways.
Kim I; Choi S; Kim S
BMC Bioinformatics; 2018 Feb; 19(Suppl 1):42. PubMed ID: 29504910
[TBL] [Abstract][Full Text] [Related]
32. Group Lasso Regularized Deep Learning for Cancer Prognosis from Multi-Omics and Clinical Features.
Xie G; Dong C; Kong Y; Zhong JF; Li M; Wang K
Genes (Basel); 2019 Mar; 10(3):. PubMed ID: 30901858
[TBL] [Abstract][Full Text] [Related]
33. Identification of miRNA-Mediated Subpathways as Prostate Cancer Biomarkers Based on Topological Inference in a Machine Learning Process Using Integrated Gene and miRNA Expression Data.
Ning Z; Yu S; Zhao Y; Sun X; Wu H; Yu X
Front Genet; 2021; 12():656526. PubMed ID: 33841512
[TBL] [Abstract][Full Text] [Related]
34. Capsule Network Based Modeling of Multi-omics Data for Discovery of Breast Cancer-Related Genes.
Peng C; Zheng Y; Huang DS
IEEE/ACM Trans Comput Biol Bioinform; 2020; 17(5):1605-1612. PubMed ID: 30969931
[TBL] [Abstract][Full Text] [Related]
35. Identifying subpathway signatures for individualized anticancer drug response by integrating multi-omics data.
Xu Y; Dong Q; Li F; Xu Y; Hu C; Wang J; Shang D; Zheng X; Yang H; Zhang C; Shao M; Meng M; Xiong Z; Li X; Zhang Y
J Transl Med; 2019 Aug; 17(1):255. PubMed ID: 31387579
[TBL] [Abstract][Full Text] [Related]
36. Integrated genomic analysis for prediction of survival for patients with liver cancer using The Cancer Genome Atlas.
Song YZ; Li X; Li W; Wang Z; Li K; Xie FL; Zhang F
World J Gastroenterol; 2018 Jul; 24(28):3145-3154. PubMed ID: 30065560
[TBL] [Abstract][Full Text] [Related]
37. Diagnostic classification of cancers using extreme gradient boosting algorithm and multi-omics data.
Ma B; Meng F; Yan G; Yan H; Chai B; Song F
Comput Biol Med; 2020 Jun; 121():103761. PubMed ID: 32339094
[TBL] [Abstract][Full Text] [Related]
38. Attention-based GCN integrates multi-omics data for breast cancer subtype classification and patient-specific gene marker identification.
Guo H; Lv X; Li Y; Li M
Brief Funct Genomics; 2023 Nov; 22(5):463-474. PubMed ID: 37114942
[TBL] [Abstract][Full Text] [Related]
39. NCC-AUC: an AUC optimization method to identify multi-biomarker panel for cancer prognosis from genomic and clinical data.
Zou M; Liu Z; Zhang XS; Wang Y
Bioinformatics; 2015 Oct; 31(20):3330-8. PubMed ID: 26092859
[TBL] [Abstract][Full Text] [Related]
40. -Omics biomarker identification pipeline for translational medicine.
Bravo-Merodio L; Williams JA; Gkoutos GV; Acharjee A
J Transl Med; 2019 May; 17(1):155. PubMed ID: 31088492
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
