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For: Zhong Y, Xuan P, Wang X, Zhang T, Li J, Liu Y, Zhang W. A non-negative matrix factorization based method for predicting disease-associated miRNAs in miRNA-disease bilayer network. Bioinformatics 2017;34:267-277. [PMID: 28968753 DOI: 10.1093/bioinformatics/btx546] [Citation(s) in RCA: 42] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2017] [Revised: 07/23/2017] [Accepted: 08/31/2017] [Indexed: 02/05/2023]  Open
Number Cited by Other Article(s)
1
Ai N, Yuan H, Liang Y, Lu S, Ouyang D, Lai QH, Lai LL. Multi-View Multiattention Graph Learning With Stack Deep Matrix Factorization for circRNA-Drug Sensitivity Association Identification. IEEE J Biomed Health Inform 2024;28:7670-7682. [PMID: 39186430 DOI: 10.1109/jbhi.2024.3431693] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/28/2024]
2
Chu S, Duan G, Yan C. PGCNMDA: Learning node representations along paths with graph convolutional network for predicting miRNA-disease associations. Methods 2024;229:71-81. [PMID: 38909974 DOI: 10.1016/j.ymeth.2024.06.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2024] [Revised: 05/26/2024] [Accepted: 06/16/2024] [Indexed: 06/25/2024]  Open
3
Ji C, Yu N, Wang Y, Ni J, Zheng C. SGLMDA: A Subgraph Learning-Based Method for miRNA-Disease Association Prediction. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2024;21:1191-1201. [PMID: 38446654 DOI: 10.1109/tcbb.2024.3373772] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/08/2024]
4
Long S, Tang X, Si X, Kong T, Zhu Y, Wang C, Qi C, Mu Z, Liu J. TriFusion enables accurate prediction of miRNA-disease association by a tri-channel fusion neural network. Commun Biol 2024;7:1067. [PMID: 39215090 PMCID: PMC11364641 DOI: 10.1038/s42003-024-06734-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2024] [Accepted: 08/13/2024] [Indexed: 09/04/2024]  Open
5
Xuan P, Wang X, Cui H, Meng X, Nakaguchi T, Zhang T. Meta-Path Semantic and Global-Local Representation Learning Enhanced Graph Convolutional Model for Disease-Related miRNA Prediction. IEEE J Biomed Health Inform 2024;28:4306-4316. [PMID: 38709611 DOI: 10.1109/jbhi.2024.3397003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
6
Sheng N, Xie X, Wang Y, Huang L, Zhang S, Gao L, Wang H. A Survey of Deep Learning for Detecting miRNA- Disease Associations: Databases, Computational Methods, Challenges, and Future Directions. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2024;21:328-347. [PMID: 38194377 DOI: 10.1109/tcbb.2024.3351752] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/11/2024]
7
Xuan P, Xiu J, Cui H, Zhang X, Nakaguchi T, Zhang T. Complementary feature learning across multiple heterogeneous networks and multimodal attribute learning for predicting disease-related miRNAs. iScience 2024;27:108639. [PMID: 38303724 PMCID: PMC10831890 DOI: 10.1016/j.isci.2023.108639] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Revised: 11/02/2023] [Accepted: 12/01/2023] [Indexed: 02/03/2024]  Open
8
Jin Z, Wang M, Tang C, Zheng X, Zhang W, Sha X, An S. Predicting miRNA-disease association via graph attention learning and multiplex adaptive modality fusion. Comput Biol Med 2024;169:107904. [PMID: 38181611 DOI: 10.1016/j.compbiomed.2023.107904] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Revised: 12/12/2023] [Accepted: 12/23/2023] [Indexed: 01/07/2024]
9
Chang Z, Zhu R, Liu J, Shang J, Dai L. HGSMDA: miRNA-Disease Association Prediction Based on HyperGCN and Sørensen-Dice Loss. Noncoding RNA 2024;10:9. [PMID: 38392964 PMCID: PMC10893088 DOI: 10.3390/ncrna10010009] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Revised: 01/19/2024] [Accepted: 01/24/2024] [Indexed: 02/25/2024]  Open
10
Qiao LJ, Gao Z, Ji CM, Liu ZH, Zheng CH, Wang YT. Potential circRNA-Disease Association Prediction Using DeepWalk and Nonnegative Matrix Factorization. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2023;20:3154-3162. [PMID: 37018084 DOI: 10.1109/tcbb.2023.3264466] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
11
Ai N, Liang Y, Yuan H, Ouyang D, Xie S, Liu X. GDCL-NcDA: identifying non-coding RNA-disease associations via contrastive learning between deep graph learning and deep matrix factorization. BMC Genomics 2023;24:424. [PMID: 37501127 PMCID: PMC10373414 DOI: 10.1186/s12864-023-09501-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Accepted: 07/02/2023] [Indexed: 07/29/2023]  Open
12
Hu X, Yin Z, Zeng Z, Peng Y. Prediction of miRNA-Disease Associations by Cascade Forest Model Based on Stacked Autoencoder. Molecules 2023;28:5013. [PMID: 37446675 DOI: 10.3390/molecules28135013] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 06/23/2023] [Accepted: 06/24/2023] [Indexed: 07/15/2023]  Open
13
Chen M, Deng Y, Li Z, Ye Y, He Z. KATZNCP: a miRNA-disease association prediction model integrating KATZ algorithm and network consistency projection. BMC Bioinformatics 2023;24:229. [PMID: 37268893 DOI: 10.1186/s12859-023-05365-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2022] [Accepted: 05/26/2023] [Indexed: 06/04/2023]  Open
14
Huang L, Zhang L, Chen X. Updated review of advances in microRNAs and complex diseases: towards systematic evaluation of computational models. Brief Bioinform 2022;23:6712303. [PMID: 36151749 DOI: 10.1093/bib/bbac407] [Citation(s) in RCA: 67] [Impact Index Per Article: 22.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2022] [Revised: 08/11/2022] [Accepted: 08/20/2022] [Indexed: 12/14/2022]  Open
15
Lu X, Li J, Zhu Z, Yuan Y, Chen G, He K. Predicting miRNA-Disease Associations via Combining Probability Matrix Feature Decomposition With Neighbor Learning. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2022;19:3160-3170. [PMID: 34260356 DOI: 10.1109/tcbb.2021.3097037] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
16
Feitosa RM, Prieto-Oliveira P, Brentani H, Machado-Lima A. MicroRNA target prediction tools for animals: Where we are at and where we are going to - A systematic review. Comput Biol Chem 2022;100:107729. [DOI: 10.1016/j.compbiolchem.2022.107729] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 07/08/2022] [Accepted: 07/09/2022] [Indexed: 11/26/2022]
17
MHDMF: Prediction of miRNA-disease associations based on Deep Matrix Factorization with Multi-source Graph Convolutional Network. Comput Biol Med 2022;149:106069. [PMID: 36115300 DOI: 10.1016/j.compbiomed.2022.106069] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Revised: 07/31/2022] [Accepted: 08/27/2022] [Indexed: 11/24/2022]
18
Wei Z, Yao D, Zhan X, Zhang S. A clustering-based sampling method for miRNA-disease association prediction. Front Genet 2022;13:995535. [PMID: 36176298 PMCID: PMC9513605 DOI: 10.3389/fgene.2022.995535] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2022] [Accepted: 08/08/2022] [Indexed: 11/13/2022]  Open
19
Huang L, Zhang L, Chen X. Updated review of advances in microRNAs and complex diseases: taxonomy, trends and challenges of computational models. Brief Bioinform 2022;23:6686738. [PMID: 36056743 DOI: 10.1093/bib/bbac358] [Citation(s) in RCA: 70] [Impact Index Per Article: 23.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 07/24/2022] [Accepted: 07/30/2022] [Indexed: 12/12/2022]  Open
20
Pan C, Poddar A, Mukherjee R, Ray AK. Impact of categorical and numerical features in ensemble machine learning frameworks for heart disease prediction. Biomed Signal Process Control 2022. [DOI: 10.1016/j.bspc.2022.103666] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
21
Yu L, Zheng Y, Ju B, Ao C, Gao L. Research progress of miRNA-disease association prediction and comparison of related algorithms. Brief Bioinform 2022;23:6542222. [PMID: 35246678 DOI: 10.1093/bib/bbac066] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Revised: 01/30/2022] [Accepted: 02/08/2022] [Indexed: 11/13/2022]  Open
22
Gao Z, Wang YT, Wu QW, Li L, Ni JC, Zheng CH. A New Method Based on Matrix Completion and Non-Negative Matrix Factorization for Predicting Disease-Associated miRNAs. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2022;19:763-772. [PMID: 32991287 DOI: 10.1109/tcbb.2020.3027444] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
23
Ye L, Chen Y, Xu H, Wang Z, Li H, Qi J, Wang J, Yao J, Liu J, Song B. Radiomics of Contrast-Enhanced Computed Tomography: A Potential Biomarker for Pretreatment Prediction of the Response to Bacillus Calmette-Guerin Immunotherapy in Non-Muscle-Invasive Bladder Cancer. Front Cell Dev Biol 2022;10:814388. [PMID: 35281100 PMCID: PMC8914064 DOI: 10.3389/fcell.2022.814388] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2021] [Accepted: 01/10/2022] [Indexed: 11/13/2022]  Open
24
Xuan P, Wang D, Cui H, Zhang T, Nakaguchi T. Integration of pairwise neighbor topologies and miRNA family and cluster attributes for miRNA-disease association prediction. Brief Bioinform 2021;23:6385813. [PMID: 34634106 DOI: 10.1093/bib/bbab428] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Revised: 09/01/2021] [Accepted: 09/19/2021] [Indexed: 12/14/2022]  Open
25
Ding P, Ouyang W, Luo J, Kwoh CK. Heterogeneous information network and its application to human health and disease. Brief Bioinform 2021;21:1327-1346. [PMID: 31566212 DOI: 10.1093/bib/bbz091] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2019] [Revised: 06/29/2019] [Accepted: 06/30/2019] [Indexed: 12/11/2022]  Open
26
Ji C, Wang Y, Ni J, Zheng C, Su Y. Predicting miRNA-Disease Associations Based on Heterogeneous Graph Attention Networks. Front Genet 2021;12:727744. [PMID: 34512733 PMCID: PMC8424198 DOI: 10.3389/fgene.2021.727744] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2021] [Accepted: 08/02/2021] [Indexed: 11/23/2022]  Open
27
Dai Q, Chu Y, Li Z, Zhao Y, Mao X, Wang Y, Xiong Y, Wei DQ. MDA-CF: Predicting MiRNA-Disease associations based on a cascade forest model by fusing multi-source information. Comput Biol Med 2021;136:104706. [PMID: 34371319 DOI: 10.1016/j.compbiomed.2021.104706] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Revised: 07/26/2021] [Accepted: 07/26/2021] [Indexed: 01/17/2023]
28
Chu Y, Wang X, Dai Q, Wang Y, Wang Q, Peng S, Wei X, Qiu J, Salahub DR, Xiong Y, Wei DQ. MDA-GCNFTG: identifying miRNA-disease associations based on graph convolutional networks via graph sampling through the feature and topology graph. Brief Bioinform 2021;22:6261915. [PMID: 34009265 DOI: 10.1093/bib/bbab165] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Revised: 04/02/2021] [Accepted: 04/08/2021] [Indexed: 11/13/2022]  Open
29
Ji C, Gao Z, Ma X, Wu Q, Ni J, Zheng C. AEMDA: inferring miRNA-disease associations based on deep autoencoder. Bioinformatics 2021;37:66-72. [PMID: 32726399 DOI: 10.1093/bioinformatics/btaa670] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2020] [Revised: 05/27/2020] [Accepted: 07/20/2020] [Indexed: 12/19/2022]  Open
30
Chen H, Guo R, Li G, Zhang W, Zhang Z. Comparative analysis of similarity measurements in miRNAs with applications to miRNA-disease association predictions. BMC Bioinformatics 2020;21:176. [PMID: 32366225 PMCID: PMC7199309 DOI: 10.1186/s12859-020-3515-9] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2019] [Accepted: 04/23/2020] [Indexed: 12/14/2022]  Open
31
Wu Q, Wang Y, Gao Z, Ni J, Zheng C. MSCHLMDA: Multi-Similarity Based Combinative Hypergraph Learning for Predicting MiRNA-Disease Association. Front Genet 2020;11:354. [PMID: 32351545 PMCID: PMC7174776 DOI: 10.3389/fgene.2020.00354] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2019] [Accepted: 03/23/2020] [Indexed: 12/17/2022]  Open
32
Gao Z, Wang YT, Wu QW, Ni JC, Zheng CH. Graph regularized L2,1-nonnegative matrix factorization for miRNA-disease association prediction. BMC Bioinformatics 2020;21:61. [PMID: 32070280 PMCID: PMC7029547 DOI: 10.1186/s12859-020-3409-x] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2019] [Accepted: 02/11/2020] [Indexed: 01/24/2023]  Open
33
Zhang Y, Chen M, Cheng X, Chen Z. LSGSP: a novel miRNA-disease association prediction model using a Laplacian score of the graphs and space projection federated method. RSC Adv 2019;9:29747-29759. [PMID: 35531537 PMCID: PMC9071959 DOI: 10.1039/c9ra05554a] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2019] [Accepted: 09/09/2019] [Indexed: 12/31/2022]  Open
34
Predicting miRNA-Disease Associations by Incorporating Projections in Low-Dimensional Space and Local Topological Information. Genes (Basel) 2019;10:genes10090685. [PMID: 31500152 PMCID: PMC6770973 DOI: 10.3390/genes10090685] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2019] [Revised: 08/31/2019] [Accepted: 09/03/2019] [Indexed: 12/14/2022]  Open
35
Prediction of Disease-related microRNAs through Integrating Attributes of microRNA Nodes and Multiple Kinds of Connecting Edges. Molecules 2019;24:molecules24173099. [PMID: 31455026 PMCID: PMC6749327 DOI: 10.3390/molecules24173099] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2019] [Revised: 08/09/2019] [Accepted: 08/14/2019] [Indexed: 11/17/2022]  Open
36
Inferring the Disease-Associated miRNAs Based on Network Representation Learning and Convolutional Neural Networks. Int J Mol Sci 2019;20:ijms20153648. [PMID: 31349729 PMCID: PMC6696449 DOI: 10.3390/ijms20153648] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2019] [Revised: 07/17/2019] [Accepted: 07/18/2019] [Indexed: 02/06/2023]  Open
37
Wei H, Liu B. iCircDA-MF: identification of circRNA-disease associations based on matrix factorization. Brief Bioinform 2019;21:1356-1367. [DOI: 10.1093/bib/bbz057] [Citation(s) in RCA: 68] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2019] [Revised: 03/13/2019] [Accepted: 04/17/2019] [Indexed: 12/19/2022]  Open
38
Chen M, Zhang Y, Li A, Li Z, Liu W, Chen Z. Bipartite Heterogeneous Network Method Based on Co-neighbor for MiRNA-Disease Association Prediction. Front Genet 2019;10:385. [PMID: 31080459 PMCID: PMC6497741 DOI: 10.3389/fgene.2019.00385] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2018] [Accepted: 04/10/2019] [Indexed: 12/22/2022]  Open
39
Long Noncoding RNA and Protein Interactions: From Experimental Results to Computational Models Based on Network Methods. Int J Mol Sci 2019;20:ijms20061284. [PMID: 30875752 PMCID: PMC6471543 DOI: 10.3390/ijms20061284] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2019] [Revised: 03/09/2019] [Accepted: 03/11/2019] [Indexed: 01/13/2023]  Open
40
Xuan P, Dong Y, Guo Y, Zhang T, Liu Y. Dual Convolutional Neural Network Based Method for Predicting Disease-Related miRNAs. Int J Mol Sci 2018;19:ijms19123732. [PMID: 30477152 PMCID: PMC6321160 DOI: 10.3390/ijms19123732] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2018] [Revised: 11/15/2018] [Accepted: 11/19/2018] [Indexed: 02/07/2023]  Open
41
Xuan P, Shen T, Wang X, Zhang T, Zhang W. Inferring disease-associated microRNAs in heterogeneous networks with node attributes. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2018;17:1019-1031. [PMID: 30281474 DOI: 10.1109/tcbb.2018.2872574] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
42
Chen X, Yin J, Qu J, Huang L. MDHGI: Matrix Decomposition and Heterogeneous Graph Inference for miRNA-disease association prediction. PLoS Comput Biol 2018;14:e1006418. [PMID: 30142158 PMCID: PMC6126877 DOI: 10.1371/journal.pcbi.1006418] [Citation(s) in RCA: 264] [Impact Index Per Article: 37.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2018] [Revised: 09/06/2018] [Accepted: 08/06/2018] [Indexed: 12/14/2022]  Open
43
Chen X, Qu J, Yin J. TLHNMDA: Triple Layer Heterogeneous Network Based Inference for MiRNA-Disease Association Prediction. Front Genet 2018;9:234. [PMID: 30018632 PMCID: PMC6038677 DOI: 10.3389/fgene.2018.00234] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2017] [Accepted: 06/12/2018] [Indexed: 12/12/2022]  Open
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Chen M, Peng Y, Li A, Li Z, Deng Y, Liu W, Liao B, Dai C. A novel information diffusion method based on network consistency for identifying disease related microRNAs. RSC Adv 2018;8:36675-36690. [PMID: 35558942 PMCID: PMC9088870 DOI: 10.1039/c8ra07519k] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2018] [Accepted: 10/17/2018] [Indexed: 12/27/2022]  Open
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