127 related articles for article (PubMed ID: 29237571)
1. Identification of genes related to proliferative diabetic retinopathy through RWR algorithm based on protein-protein interaction network.
Zhang J; Suo Y; Liu M; Xu X
Biochim Biophys Acta Mol Basis Dis; 2018 Jun; 1864(6 Pt B):2369-2375. PubMed ID: 29237571
[TBL] [Abstract][Full Text] [Related]
2. Identification of proliferative diabetic retinopathy-associated genes on the protein-protein interaction network by using heat diffusion algorithm.
Zhang J; Zhang M; Zhao H; Xu X
Biochim Biophys Acta Mol Basis Dis; 2020 Oct; 1866(10):165794. PubMed ID: 32278010
[TBL] [Abstract][Full Text] [Related]
3. Identification of the aberrantly methylated differentially expressed genes in proliferative diabetic retinopathy.
Miao A; Lu J; Wang Y; Mao S; Cui Y; Pan J; Li L; Luo Y
Exp Eye Res; 2020 Oct; 199():108141. PubMed ID: 32721427
[TBL] [Abstract][Full Text] [Related]
4. Mining the proliferative diabetic retinopathy-associated genes and pathways by integrated bioinformatic analysis.
Sun H; Cheng Y; Yan Z; Liu X; Zhang J
Int Ophthalmol; 2020 Feb; 40(2):269-279. PubMed ID: 31953631
[TBL] [Abstract][Full Text] [Related]
5. Network-based method for mining novel HPV infection related genes using random walk with restart algorithm.
Zhu L; Su F; Xu Y; Zou Q
Biochim Biophys Acta Mol Basis Dis; 2018 Jun; 1864(6 Pt B):2376-2383. PubMed ID: 29197659
[TBL] [Abstract][Full Text] [Related]
6. Gene gravity-like algorithm for disease gene prediction based on phenotype-specific network.
Lin L; Yang T; Fang L; Yang J; Yang F; Zhao J
BMC Syst Biol; 2017 Dec; 11(1):121. PubMed ID: 29212543
[TBL] [Abstract][Full Text] [Related]
7. Determination of Genes Related to Uveitis by Utilization of the Random Walk with Restart Algorithm on a Protein-Protein Interaction Network.
Lu S; Yan Y; Li Z; Chen L; Yang J; Zhang Y; Wang S; Liu L
Int J Mol Sci; 2017 May; 18(5):. PubMed ID: 28505077
[TBL] [Abstract][Full Text] [Related]
8. A network-based method using a random walk with restart algorithm and screening tests to identify novel genes associated with Menière's disease.
Li L; Wang Y; An L; Kong X; Huang T
PLoS One; 2017; 12(8):e0182592. PubMed ID: 28787010
[TBL] [Abstract][Full Text] [Related]
9. A computational method using the random walk with restart algorithm for identifying novel epigenetic factors.
Li J; Chen L; Wang S; Zhang Y; Kong X; Huang T; Cai YD
Mol Genet Genomics; 2018 Feb; 293(1):293-301. PubMed ID: 28932904
[TBL] [Abstract][Full Text] [Related]
10. Identifying novel fruit-related genes in Arabidopsis thaliana based on the random walk with restart algorithm.
Zhang Y; Dai L; Liu Y; Zhang Y; Wang S
PLoS One; 2017; 12(5):e0177017. PubMed ID: 28472169
[TBL] [Abstract][Full Text] [Related]
11. Unveiling the molecular complexity of proliferative diabetic retinopathy through scRNA-seq, AlphaFold 2, and machine learning.
Wang J; Sun H; Mou L; Lu Y; Wu Z; Pu Z; Yang MM
Front Endocrinol (Lausanne); 2024; 15():1382896. PubMed ID: 38800474
[TBL] [Abstract][Full Text] [Related]
12. Prioritization of candidate disease genes by enlarging the seed set and fusing information of the network topology and gene expression.
Zhang SW; Shao DD; Zhang SY; Wang YB
Mol Biosyst; 2014 Jun; 10(6):1400-8. PubMed ID: 24695957
[TBL] [Abstract][Full Text] [Related]
13. Identification and comprehensive analysis of ferroptosis-related genes as potential biomarkers for the diagnosis and treatment of proliferative diabetic retinopathy by bioinformatics methods.
Cao D; Wang C; Zhou L
Exp Eye Res; 2023 Jul; 232():109513. PubMed ID: 37207868
[TBL] [Abstract][Full Text] [Related]
14. The integrated transcriptome bioinformatics analysis identifies key genes and cellular components for proliferative diabetic retinopathy.
Gao N; Hao S; Huang G; Hao W; Su L
PLoS One; 2022; 17(11):e0277952. PubMed ID: 36409751
[TBL] [Abstract][Full Text] [Related]
15. Exploring the Immune Infiltration Landscape and M2 Macrophage-Related Biomarkers of Proliferative Diabetic Retinopathy.
Meng Z; Chen Y; Wu W; Yan B; Meng Y; Liang Y; Yao X; Luo J
Front Endocrinol (Lausanne); 2022; 13():841813. PubMed ID: 35692390
[TBL] [Abstract][Full Text] [Related]
16. Identification of immune associated potential molecular targets in proliferative diabetic retinopathy.
Gao Y; Xue M; Dai B; Tang Y; Liu J; Zhao C; Meng H; Yan F; Zhu X; Lu Y; Ge Y
BMC Ophthalmol; 2023 Jan; 23(1):27. PubMed ID: 36658547
[TBL] [Abstract][Full Text] [Related]
17. Inferring Novel Tumor Suppressor Genes with a Protein-Protein Interaction Network and Network Diffusion Algorithms.
Chen L; Zhang YH; Zhang Z; Huang T; Cai YD
Mol Ther Methods Clin Dev; 2018 Sep; 10():57-67. PubMed ID: 30069494
[TBL] [Abstract][Full Text] [Related]
18. Mining disease genes using integrated protein-protein interaction and gene-gene co-regulation information.
Li J; Wang L; Guo M; Zhang R; Dai Q; Liu X; Wang C; Teng Z; Xuan P; Zhang M
FEBS Open Bio; 2015; 5():251-6. PubMed ID: 25870785
[TBL] [Abstract][Full Text] [Related]
19. NLRP3 inflammasome activation is associated with proliferative diabetic retinopathy.
Loukovaara S; Piippo N; Kinnunen K; Hytti M; Kaarniranta K; Kauppinen A
Acta Ophthalmol; 2017 Dec; 95(8):803-808. PubMed ID: 28271611
[TBL] [Abstract][Full Text] [Related]
20. BMRF-MI: integrative identification of protein interaction network by modeling the gene dependency.
Shi X; Wang X; Shajahan A; Hilakivi-Clarke L; Clarke R; Xuan J
BMC Genomics; 2015; 16 Suppl 7(Suppl 7):S10. PubMed ID: 26099273
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]