251 related articles for article (PubMed ID: 32029856)
1. Integrating random walk with restart and k-Nearest Neighbor to identify novel circRNA-disease association.
Lei X; Bian C
Sci Rep; 2020 Feb; 10(1):1943. PubMed ID: 32029856
[TBL] [Abstract][Full Text] [Related]
2. Integrating Bipartite Network Projection and KATZ Measure to Identify Novel CircRNA-Disease Associations.
Zhao Q; Yang Y; Ren G; Ge E; Fan C
IEEE Trans Nanobioscience; 2019 Oct; 18(4):578-584. PubMed ID: 31199265
[TBL] [Abstract][Full Text] [Related]
3. Prediction of circRNA-Disease Associations Based on the Combination of Multi-Head Graph Attention Network and Graph Convolutional Network.
Cao R; He C; Wei P; Su Y; Xia J; Zheng C
Biomolecules; 2022 Jul; 12(7):. PubMed ID: 35883487
[TBL] [Abstract][Full Text] [Related]
4. GGAECDA: Predicting circRNA-disease associations using graph autoencoder based on graph representation learning.
Li G; Lin Y; Luo J; Xiao Q; Liang C
Comput Biol Chem; 2022 Aug; 99():107722. PubMed ID: 35810557
[TBL] [Abstract][Full Text] [Related]
5. Fusion of multiple heterogeneous networks for predicting circRNA-disease associations.
Deng L; Zhang W; Shi Y; Tang Y
Sci Rep; 2019 Jul; 9(1):9605. PubMed ID: 31270357
[TBL] [Abstract][Full Text] [Related]
6. Predicting human disease-associated circRNAs based on locality-constrained linear coding.
Ge E; Yang Y; Gang M; Fan C; Zhao Q
Genomics; 2020 Mar; 112(2):1335-1342. PubMed ID: 31394170
[TBL] [Abstract][Full Text] [Related]
7. GCNCDA: A new method for predicting circRNA-disease associations based on Graph Convolutional Network Algorithm.
Wang L; You ZH; Li YM; Zheng K; Huang YA
PLoS Comput Biol; 2020 May; 16(5):e1007568. PubMed ID: 32433655
[TBL] [Abstract][Full Text] [Related]
8. DWNN-RLS: regularized least squares method for predicting circRNA-disease associations.
Yan C; Wang J; Wu FX
BMC Bioinformatics; 2018 Dec; 19(Suppl 19):520. PubMed ID: 30598076
[TBL] [Abstract][Full Text] [Related]
9. CRPGCN: predicting circRNA-disease associations using graph convolutional network based on heterogeneous network.
Ma Z; Kuang Z; Deng L
BMC Bioinformatics; 2021 Nov; 22(1):551. PubMed ID: 34772332
[TBL] [Abstract][Full Text] [Related]
10. Predicting novel CircRNA-disease associations based on random walk and logistic regression model.
Ding Y; Chen B; Lei X; Liao B; Wu FX
Comput Biol Chem; 2020 May; 87():107287. PubMed ID: 32446243
[TBL] [Abstract][Full Text] [Related]
11. An ensemble approach for CircRNA-disease association prediction based on autoencoder and deep neural network.
Deepthi K; Jereesh AS
Gene; 2020 Dec; 762():145040. PubMed ID: 32777520
[TBL] [Abstract][Full Text] [Related]
12. Combining K Nearest Neighbor With Nonnegative Matrix Factorization for Predicting Circrna-Disease Associations.
Wang MN; Xie XJ; You ZH; Wong L; Li LP; Chen ZH
IEEE/ACM Trans Comput Biol Bioinform; 2023; 20(5):2610-2618. PubMed ID: 35675235
[TBL] [Abstract][Full Text] [Related]
13. iCDA-CGR: Identification of circRNA-disease associations based on Chaos Game Representation.
Zheng K; You ZH; Li JQ; Wang L; Guo ZH; Huang YA
PLoS Comput Biol; 2020 May; 16(5):e1007872. PubMed ID: 32421715
[TBL] [Abstract][Full Text] [Related]
14. Inferring Potential CircRNA-Disease Associations via Deep Autoencoder-Based Classification.
Deepthi K; Jereesh AS
Mol Diagn Ther; 2021 Jan; 25(1):87-97. PubMed ID: 33156515
[TBL] [Abstract][Full Text] [Related]
15. GBDTCDA: Predicting circRNA-disease Associations Based on Gradient Boosting Decision Tree with Multiple Biological Data Fusion.
Lei X; Fang Z
Int J Biol Sci; 2019; 15(13):2911-2924. PubMed ID: 31853227
[TBL] [Abstract][Full Text] [Related]
16. PCirc: random forest-based plant circRNA identification software.
Yin S; Tian X; Zhang J; Sun P; Li G
BMC Bioinformatics; 2021 Jan; 22(1):10. PubMed ID: 33407069
[TBL] [Abstract][Full Text] [Related]
17. MNCLCDA: predicting circRNA-drug sensitivity associations by using mixed neighbourhood information and contrastive learning.
Li G; Zeng F; Luo J; Liang C; Xiao Q
BMC Med Inform Decis Mak; 2023 Dec; 23(1):291. PubMed ID: 38110886
[TBL] [Abstract][Full Text] [Related]
18. Prediction of circRNA-disease associations based on inductive matrix completion.
Li M; Liu M; Bin Y; Xia J
BMC Med Genomics; 2020 Apr; 13(Suppl 5):42. PubMed ID: 32241268
[TBL] [Abstract][Full Text] [Related]
19. SGANRDA: semi-supervised generative adversarial networks for predicting circRNA-disease associations.
Wang L; Yan X; You ZH; Zhou X; Li HY; Huang YA
Brief Bioinform; 2021 Sep; 22(5):. PubMed ID: 33734296
[TBL] [Abstract][Full Text] [Related]
20. iCDA-CMG: identifying circRNA-disease associations by federating multi-similarity fusion and collective matrix completion.
Xiao Q; Zhong J; Tang X; Luo J
Mol Genet Genomics; 2021 Jan; 296(1):223-233. PubMed ID: 33159254
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
