157 related articles for article (PubMed ID: 34880275)
1. Novel cancer subtyping method based on patient-specific gene regulatory network.
Nakazawa MA; Tamada Y; Tanaka Y; Ikeguchi M; Higashihara K; Okuno Y
Sci Rep; 2021 Dec; 11(1):23653. PubMed ID: 34880275
[TBL] [Abstract][Full Text] [Related]
2. Improvement of cancer subtype prediction by incorporating transcriptome expression data and heterogeneous biological networks.
Guo Y; Qi Y; Li Z; Shang X
BMC Med Genomics; 2018 Dec; 11(Suppl 6):119. PubMed ID: 30598111
[TBL] [Abstract][Full Text] [Related]
3. A network-assisted co-clustering algorithm to discover cancer subtypes based on gene expression.
Liu Y; Gu Q; Hou JP; Han J; Ma J
BMC Bioinformatics; 2014 Feb; 15():37. PubMed ID: 24491042
[TBL] [Abstract][Full Text] [Related]
4. Network based stratification of major cancers by integrating somatic mutation and gene expression data.
He Z; Zhang J; Yuan X; Liu Z; Liu B; Tuo S; Liu Y
PLoS One; 2017; 12(5):e0177662. PubMed ID: 28520777
[TBL] [Abstract][Full Text] [Related]
5. HSSG: Identification of Cancer Subtypes Based on Heterogeneity Score of A Single Gene.
Pang S; Wu W; Zhang Y; Wang S; Niu M; Zhang K; Yin W
Cells; 2022 Aug; 11(15):. PubMed ID: 35954300
[TBL] [Abstract][Full Text] [Related]
6. Weighted dimensionality reduction and robust Gaussian mixture model based cancer patient subtyping from gene expression data.
Rafique O; Mir AH
J Biomed Inform; 2020 Dec; 112():103620. PubMed ID: 33188907
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. Fast dimension reduction and integrative clustering of multi-omics data using low-rank approximation: application to cancer molecular classification.
Wu D; Wang D; Zhang MQ; Gu J
BMC Genomics; 2015 Dec; 16():1022. PubMed ID: 26626453
[TBL] [Abstract][Full Text] [Related]
9. Integrated multi-omics analysis of ovarian cancer using variational autoencoders.
Hira MT; Razzaque MA; Angione C; Scrivens J; Sawan S; Sarker M
Sci Rep; 2021 Mar; 11(1):6265. PubMed ID: 33737557
[TBL] [Abstract][Full Text] [Related]
10. Subtype identification from heterogeneous TCGA datasets on a genomic scale by multi-view clustering with enhanced consensus.
Cai M; Li L
BMC Med Genomics; 2017 Dec; 10(Suppl 4):75. PubMed ID: 29322925
[TBL] [Abstract][Full Text] [Related]
11. Cancer subtyping with heterogeneous multi-omics data via hierarchical multi-kernel learning.
Wei Y; Li L; Zhao X; Yang H; Sa J; Cao H; Cui Y
Brief Bioinform; 2023 Jan; 24(1):. PubMed ID: 36433785
[TBL] [Abstract][Full Text] [Related]
12. Interactive gene identification for cancer subtyping based on multi-omics clustering.
Ye X; Shi T; Cui Y; Sakurai T
Methods; 2023 Mar; 211():61-67. PubMed ID: 36804215
[TBL] [Abstract][Full Text] [Related]
13. Subtype-DCC: decoupled contrastive clustering method for cancer subtype identification based on multi-omics data.
Zhao J; Zhao B; Song X; Lyu C; Chen W; Xiong Y; Wei DQ
Brief Bioinform; 2023 Mar; 24(2):. PubMed ID: 36702755
[TBL] [Abstract][Full Text] [Related]
14. Identifying Cancer Subtypes from miRNA-TF-mRNA Regulatory Networks and Expression Data.
Xu T; Le TD; Liu L; Wang R; Sun B; Li J
PLoS One; 2016; 11(4):e0152792. PubMed ID: 27035433
[TBL] [Abstract][Full Text] [Related]
15. Survey and comparative assessments of computational multi-omics integrative methods with multiple regulatory networks identifying distinct tumor compositions across pan-cancer data sets.
Wei Z; Zhang Y; Weng W; Chen J; Cai H
Brief Bioinform; 2021 May; 22(3):. PubMed ID: 32533167
[TBL] [Abstract][Full Text] [Related]
16. Clinical Parameters Outperform Molecular Subtypes for Predicting Outcome in Bladder Cancer: Results from Multiple Cohorts, Including TCGA.
Morera DS; Hasanali SL; Belew D; Ghosh S; Klaassen Z; Jordan AR; Wang J; Terris MK; Bollag RJ; Merseburger AS; Stenzl A; Soloway MS; Lokeshwar VB
J Urol; 2020 Jan; 203(1):62-72. PubMed ID: 31112107
[TBL] [Abstract][Full Text] [Related]
17. A unified graph model based on molecular data binning for disease subtyping.
Hassan Zada MS; Yuan B; Khan WA; Anjum A; Reiff-Marganiec S; Saleem R
J Biomed Inform; 2022 Oct; 134():104187. PubMed ID: 36055637
[TBL] [Abstract][Full Text] [Related]
18. Identification of cancer subtypes from single-cell RNA-seq data using a consensus clustering method.
Gan Y; Li N; Zou G; Xin Y; Guan J
BMC Med Genomics; 2018 Dec; 11(Suppl 6):117. PubMed ID: 30598115
[TBL] [Abstract][Full Text] [Related]
19. HCNM: Heterogeneous Correlation Network Model for Multi-level Integrative Study of Multi-omics Data for Cancer Subtype Prediction.
Vangimalla RR; Sreevalsan-Nair J
Annu Int Conf IEEE Eng Med Biol Soc; 2021 Nov; 2021():1880-1886. PubMed ID: 34891654
[TBL] [Abstract][Full Text] [Related]
20. A fully Bayesian latent variable model for integrative clustering analysis of multi-type omics data.
Mo Q; Shen R; Guo C; Vannucci M; Chan KS; Hilsenbeck SG
Biostatistics; 2018 Jan; 19(1):71-86. PubMed ID: 28541380
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
