199 related articles for article (PubMed ID: 36744179)
1. Screening potential lncRNA biomarkers for breast cancer and colorectal cancer combining random walk and logistic matrix factorization.
Li S; Chang M; Tong L; Wang Y; Wang M; Wang F
Front Genet; 2022; 13():1023615. PubMed ID: 36744179
[TBL] [Abstract][Full Text] [Related]
2. IDSSIM: an lncRNA functional similarity calculation model based on an improved disease semantic similarity method.
Fan W; Shang J; Li F; Sun Y; Yuan S; Liu JX
BMC Bioinformatics; 2020 Jul; 21(1):339. PubMed ID: 32736513
[TBL] [Abstract][Full Text] [Related]
3. LDA-VGHB: identifying potential lncRNA-disease associations with singular value decomposition, variational graph auto-encoder and heterogeneous Newton boosting machine.
Peng L; Huang L; Su Q; Tian G; Chen M; Han G
Brief Bioinform; 2023 Nov; 25(1):. PubMed ID: 38127089
[TBL] [Abstract][Full Text] [Related]
4. Finding Lung-Cancer-Related lncRNAs Based on Laplacian Regularized Least Squares With Unbalanced Bi-Random Walk.
Guo Z; Hui Y; Kong F; Lin X
Front Genet; 2022; 13():933009. PubMed ID: 35938010
[TBL] [Abstract][Full Text] [Related]
5. Detecting lncRNA-Cancer Associations by Combining miRNAs, Genes, and Prognosis With Matrix Factorization.
Yan H; Chai H; Zhao H
Front Genet; 2021; 12():639872. PubMed ID: 34262591
[No Abstract] [Full Text] [Related]
6. Predicting potential lncRNA biomarkers for lung cancer and neuroblastoma based on an ensemble of a deep neural network and LightGBM.
Su Z; Lu H; Wu Y; Li Z; Duan L
Front Genet; 2023; 14():1238095. PubMed ID: 37655066
[No Abstract] [Full Text] [Related]
7. A random forest based computational model for predicting novel lncRNA-disease associations.
Yao D; Zhan X; Zhan X; Kwoh CK; Li P; Wang J
BMC Bioinformatics; 2020 Mar; 21(1):126. PubMed ID: 32216744
[TBL] [Abstract][Full Text] [Related]
8. GEnDDn: An lncRNA-Disease Association Identification Framework Based on Dual-Net Neural Architecture and Deep Neural Network.
Peng L; Ren M; Huang L; Chen M
Interdiscip Sci; 2024 May; ():. PubMed ID: 38733474
[TBL] [Abstract][Full Text] [Related]
9. DNILMF-LDA: Prediction of lncRNA-Disease Associations by Dual-Network Integrated Logistic Matrix Factorization and Bayesian Optimization.
Li Y; Li J; Bian N
Genes (Basel); 2019 Aug; 10(8):. PubMed ID: 31409034
[TBL] [Abstract][Full Text] [Related]
10. LDA-LNSUBRW: lncRNA-Disease Association Prediction Based on Linear Neighborhood Similarity and Unbalanced bi-Random Walk.
Xie G; Jiang J; Sun Y
IEEE/ACM Trans Comput Biol Bioinform; 2022; 19(2):989-997. PubMed ID: 32870798
[TBL] [Abstract][Full Text] [Related]
11. A Probabilistic Matrix Factorization Method for Identifying lncRNA-disease Associations.
Xuan Z; Li J; Yu J; Feng X; Zhao B; Wang L
Genes (Basel); 2019 Feb; 10(2):. PubMed ID: 30744078
[TBL] [Abstract][Full Text] [Related]
12. MSF-UBRW: An Improved Unbalanced Bi-Random Walk Method to Infer Human lncRNA-Disease Associations.
Dai L; Zhu R; Liu J; Li F; Wang J; Shang J
Genes (Basel); 2022 Nov; 13(11):. PubMed ID: 36360269
[TBL] [Abstract][Full Text] [Related]
13. IRWNRLPI: Integrating Random Walk and Neighborhood Regularized Logistic Matrix Factorization for lncRNA-Protein Interaction Prediction.
Zhao Q; Zhang Y; Hu H; Ren G; Zhang W; Liu H
Front Genet; 2018; 9():239. PubMed ID: 30023002
[TBL] [Abstract][Full Text] [Related]
14. Predicting LncRNA-Disease Association by a Random Walk With Restart on Multiplex and Heterogeneous Networks.
Yao Y; Ji B; Lv Y; Li L; Xiang J; Liao B; Gao W
Front Genet; 2021; 12():712170. PubMed ID: 34490041
[TBL] [Abstract][Full Text] [Related]
15. Finding potential lncRNA-disease associations using a boosting-based ensemble learning model.
Zhou L; Peng X; Zeng L; Peng L
Front Genet; 2024; 15():1356205. PubMed ID: 38495672
[No Abstract] [Full Text] [Related]
16. DSCMF: prediction of LncRNA-disease associations based on dual sparse collaborative matrix factorization.
Liu JX; Gao MM; Cui Z; Gao YL; Li F
BMC Bioinformatics; 2021 May; 22(Suppl 3):241. PubMed ID: 33980147
[TBL] [Abstract][Full Text] [Related]
17. A novel target convergence set based random walk with restart for prediction of potential LncRNA-disease associations.
Li J; Li X; Feng X; Wang B; Zhao B; Wang L
BMC Bioinformatics; 2019 Dec; 20(1):626. PubMed ID: 31795943
[TBL] [Abstract][Full Text] [Related]
18. Prediction of lncRNA-disease associations by integrating diverse heterogeneous information sources with RWR algorithm and positive pointwise mutual information.
Fan XN; Zhang SW; Zhang SY; Zhu K; Lu S
BMC Bioinformatics; 2019 Feb; 20(1):87. PubMed ID: 30782113
[TBL] [Abstract][Full Text] [Related]
19. iLncDA-RSN: identification of lncRNA-disease associations based on reliable similarity networks.
Li Y; Zhang M; Shang J; Li F; Ren Q; Liu JX
Front Genet; 2023; 14():1249171. PubMed ID: 37614816
[TBL] [Abstract][Full Text] [Related]
20. Prediction of lncRNA-disease association based on a Laplace normalized random walk with restart algorithm on heterogeneous networks.
Wang L; Shang M; Dai Q; He PA
BMC Bioinformatics; 2022 Jan; 23(1):5. PubMed ID: 34983367
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]