1914 related articles for article (PubMed ID: 28245811)
1. RNA-protein binding motifs mining with a new hybrid deep learning based cross-domain knowledge integration approach.
Pan X; Shen HB
BMC Bioinformatics; 2017 Feb; 18(1):136. PubMed ID: 28245811
[TBL] [Abstract][Full Text] [Related]
2. Prediction of RNA-protein sequence and structure binding preferences using deep convolutional and recurrent neural networks.
Pan X; Rijnbeek P; Yan J; Shen HB
BMC Genomics; 2018 Jul; 19(1):511. PubMed ID: 29970003
[TBL] [Abstract][Full Text] [Related]
3. RNA-binding protein recognition based on multi-view deep feature and multi-label learning.
Yang H; Deng Z; Pan X; Shen HB; Choi KS; Wang L; Wang S; Wu J
Brief Bioinform; 2021 May; 22(3):. PubMed ID: 32808039
[TBL] [Abstract][Full Text] [Related]
4. Predicting RNA-protein binding sites and motifs through combining local and global deep convolutional neural networks.
Pan X; Shen HB
Bioinformatics; 2018 Oct; 34(20):3427-3436. PubMed ID: 29722865
[TBL] [Abstract][Full Text] [Related]
5. CRIP: predicting circRNA-RBP-binding sites using a codon-based encoding and hybrid deep neural networks.
Zhang K; Pan X; Yang Y; Shen HB
RNA; 2019 Dec; 25(12):1604-1615. PubMed ID: 31537716
[TBL] [Abstract][Full Text] [Related]
6. Integrating thermodynamic and sequence contexts improves protein-RNA binding prediction.
Su Y; Luo Y; Zhao X; Liu Y; Peng J
PLoS Comput Biol; 2019 Sep; 15(9):e1007283. PubMed ID: 31483777
[TBL] [Abstract][Full Text] [Related]
7. Prediction of binding property of RNA-binding proteins using multi-sized filters and multi-modal deep convolutional neural network.
Chung T; Kim D
PLoS One; 2019; 14(4):e0216257. PubMed ID: 31026297
[TBL] [Abstract][Full Text] [Related]
8. Prediction of the RBP binding sites on lncRNAs using the high-order nucleotide encoding convolutional neural network.
Zhang SW; Wang Y; Zhang XX; Wang JQ
Anal Biochem; 2019 Oct; 583():113364. PubMed ID: 31323206
[TBL] [Abstract][Full Text] [Related]
9. ssHMM: extracting intuitive sequence-structure motifs from high-throughput RNA-binding protein data.
Heller D; Krestel R; Ohler U; Vingron M; Marsico A
Nucleic Acids Res; 2017 Nov; 45(19):11004-11018. PubMed ID: 28977546
[TBL] [Abstract][Full Text] [Related]
10. A deep boosting based approach for capturing the sequence binding preferences of RNA-binding proteins from high-throughput CLIP-seq data.
Li S; Dong F; Wu Y; Zhang S; Zhang C; Liu X; Jiang T; Zeng J
Nucleic Acids Res; 2017 Aug; 45(14):e129. PubMed ID: 28575488
[TBL] [Abstract][Full Text] [Related]
11. iDRBP_MMC: Identifying DNA-Binding Proteins and RNA-Binding Proteins Based on Multi-Label Learning Model and Motif-Based Convolutional Neural Network.
Zhang J; Chen Q; Liu B
J Mol Biol; 2020 Nov; 432(22):5860-5875. PubMed ID: 32920048
[TBL] [Abstract][Full Text] [Related]
12. A combined sequence and structure based method for discovering enriched motifs in RNA from in vivo binding data.
Polishchuk M; Paz I; Kohen R; Mesika R; Yakhini Z; Mandel-Gutfreund Y
Methods; 2017 Apr; 118-119():73-81. PubMed ID: 28274760
[TBL] [Abstract][Full Text] [Related]
13. RBPsuite: RNA-protein binding sites prediction suite based on deep learning.
Pan X; Fang Y; Li X; Yang Y; Shen HB
BMC Genomics; 2020 Dec; 21(1):884. PubMed ID: 33297946
[TBL] [Abstract][Full Text] [Related]
14. IPMiner: hidden ncRNA-protein interaction sequential pattern mining with stacked autoencoder for accurate computational prediction.
Pan X; Fan YX; Yan J; Shen HB
BMC Genomics; 2016 Aug; 17():582. PubMed ID: 27506469
[TBL] [Abstract][Full Text] [Related]
15. econvRBP: Improved ensemble convolutional neural networks for RNA binding protein prediction directly from sequence.
Zhao Y; Du X
Methods; 2020 Oct; 181-182():15-23. PubMed ID: 31513916
[TBL] [Abstract][Full Text] [Related]
16. Deep neural networks for inferring binding sites of RNA-binding proteins by using distributed representations of RNA primary sequence and secondary structure.
Deng L; Liu Y; Shi Y; Zhang W; Yang C; Liu H
BMC Genomics; 2020 Dec; 21(Suppl 13):866. PubMed ID: 33334313
[TBL] [Abstract][Full Text] [Related]
17. Decoding protein binding landscape on circular RNAs with base-resolution transformer models.
Wu H; Liu X; Fang Y; Yang Y; Huang Y; Pan X; Shen HB
Comput Biol Med; 2024 Mar; 171():108175. PubMed ID: 38402841
[TBL] [Abstract][Full Text] [Related]
18. Leveraging cross-link modification events in CLIP-seq for motif discovery.
Bahrami-Samani E; Penalva LO; Smith AD; Uren PJ
Nucleic Acids Res; 2015 Jan; 43(1):95-103. PubMed ID: 25505146
[TBL] [Abstract][Full Text] [Related]
19. A deep learning method for lincRNA detection using auto-encoder algorithm.
Yu N; Yu Z; Pan Y
BMC Bioinformatics; 2017 Dec; 18(Suppl 15):511. PubMed ID: 29244011
[TBL] [Abstract][Full Text] [Related]
20. RBP-TSTL is a two-stage transfer learning framework for genome-scale prediction of RNA-binding proteins.
Peng X; Wang X; Guo Y; Ge Z; Li F; Gao X; Song J
Brief Bioinform; 2022 Jul; 23(4):. PubMed ID: 35649392
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]