177 related articles for article (PubMed ID: 37780374)
1. DeepMethylation: a deep learning based framework with GloVe and Transformer encoder for DNA methylation prediction.
Wang Z; Xiang S; Zhou C; Xu Q
PeerJ; 2023; 11():e16125. PubMed ID: 37780374
[TBL] [Abstract][Full Text] [Related]
2. EMDLP: Ensemble multiscale deep learning model for RNA methylation site prediction.
Wang H; Liu H; Huang T; Li G; Zhang L; Sun Y
BMC Bioinformatics; 2022 Jun; 23(1):221. PubMed ID: 35676633
[TBL] [Abstract][Full Text] [Related]
3. iDNA-ABT: advanced deep learning model for detecting DNA methylation with adaptive features and transductive information maximization.
Yu Y; He W; Jin J; Xiao G; Cui L; Zeng R; Wei L
Bioinformatics; 2021 Dec; 37(24):4603-4610. PubMed ID: 34601568
[TBL] [Abstract][Full Text] [Related]
4. EnAMP: A novel deep learning ensemble antibacterial peptide recognition algorithm based on multi-features.
Zhuang J; Gao W; Su R
J Bioinform Comput Biol; 2024 Feb; 22(1):2450001. PubMed ID: 38406833
[TBL] [Abstract][Full Text] [Related]
5. KGETCDA: an efficient representation learning framework based on knowledge graph encoder from transformer for predicting circRNA-disease associations.
Wu J; Ning Z; Ding Y; Wang Y; Peng Q; Fu L
Brief Bioinform; 2023 Sep; 24(5):. PubMed ID: 37587836
[TBL] [Abstract][Full Text] [Related]
6. DeepSSPred: A Deep Learning Based Sulfenylation Site Predictor Via a Novel nSegmented Optimize Federated Feature Encoder.
Khan ZU; Pi D
Protein Pept Lett; 2021; 28(6):708-721. PubMed ID: 33267753
[TBL] [Abstract][Full Text] [Related]
7. Deep-WET: a deep learning-based approach for predicting DNA-binding proteins using word embedding techniques with weighted features.
Mahmud SMH; Goh KOM; Hosen MF; Nandi D; Shoombuatong W
Sci Rep; 2024 Feb; 14(1):2961. PubMed ID: 38316843
[TBL] [Abstract][Full Text] [Related]
8. BERT-5mC: an interpretable model for predicting 5-methylcytosine sites of DNA based on BERT.
Wang S; Liu Y; Liu Y; Zhang Y; Zhu X
PeerJ; 2023; 11():e16600. PubMed ID: 38089911
[TBL] [Abstract][Full Text] [Related]
9. DeepSignal: detecting DNA methylation state from Nanopore sequencing reads using deep-learning.
Ni P; Huang N; Zhang Z; Wang DP; Liang F; Miao Y; Xiao CL; Luo F; Wang J
Bioinformatics; 2019 Nov; 35(22):4586-4595. PubMed ID: 30994904
[TBL] [Abstract][Full Text] [Related]
10. Dual encoder network with transformer-CNN for multi-organ segmentation.
Hong Z; Chen M; Hu W; Yan S; Qu A; Chen L; Chen J
Med Biol Eng Comput; 2023 Mar; 61(3):661-671. PubMed ID: 36580181
[TBL] [Abstract][Full Text] [Related]
11. A comparative study on deep learning models for text classification of unstructured medical notes with various levels of class imbalance.
Lu H; Ehwerhemuepha L; Rakovski C
BMC Med Res Methodol; 2022 Jul; 22(1):181. PubMed ID: 35780100
[TBL] [Abstract][Full Text] [Related]
12. A hybrid explainable ensemble transformer encoder for pneumonia identification from chest X-ray images.
Ukwuoma CC; Qin Z; Belal Bin Heyat M; Akhtar F; Bamisile O; Muaad AY; Addo D; Al-Antari MA
J Adv Res; 2023 Jun; 48():191-211. PubMed ID: 36084812
[TBL] [Abstract][Full Text] [Related]
13. NanoCon: contrastive learning-based deep hybrid network for nanopore methylation detection.
Yin C; Wang R; Qiao J; Shi H; Duan H; Jiang X; Teng S; Wei L
Bioinformatics; 2024 Feb; 40(2):. PubMed ID: 38305428
[TBL] [Abstract][Full Text] [Related]
14. circRNA-binding protein site prediction based on multi-view deep learning, subspace learning and multi-view classifier.
Li H; Deng Z; Yang H; Pan X; Wei Z; Shen HB; Choi KS; Wang L; Wang S; Wu J
Brief Bioinform; 2022 Jan; 23(1):. PubMed ID: 34571539
[TBL] [Abstract][Full Text] [Related]
15. DeepGpgs: a novel deep learning framework for predicting arginine methylation sites combined with Gaussian prior and gated self-attention mechanism.
Zhou H; Tan W; Shi S
Brief Bioinform; 2023 Mar; 24(2):. PubMed ID: 36694944
[TBL] [Abstract][Full Text] [Related]
16. A transformer architecture based on BERT and 2D convolutional neural network to identify DNA enhancers from sequence information.
Le NQK; Ho QT; Nguyen TT; Ou YY
Brief Bioinform; 2021 Sep; 22(5):. PubMed ID: 33539511
[TBL] [Abstract][Full Text] [Related]
17. Plant6mA: A predictor for predicting N6-methyladenine sites with lightweight structure in plant genomes.
Shi H; Li S; Su X
Methods; 2022 Aug; 204():126-131. PubMed ID: 35231584
[TBL] [Abstract][Full Text] [Related]
18. EDLm
Zhang L; Li G; Li X; Wang H; Chen S; Liu H
BMC Bioinformatics; 2021 May; 22(1):288. PubMed ID: 34051729
[TBL] [Abstract][Full Text] [Related]
19. A Unified Deep Learning Framework for Single-Cell ATAC-Seq Analysis Based on ProdDep Transformer Encoder.
Wang Z; Zhang Y; Yu Y; Zhang J; Liu Y; Zou Q
Int J Mol Sci; 2023 Mar; 24(5):. PubMed ID: 36902216
[TBL] [Abstract][Full Text] [Related]
20. DGA-5mC: A 5-methylcytosine site prediction model based on an improved DenseNet and bidirectional GRU method.
Jia J; Qin L; Lei R
Math Biosci Eng; 2023 Mar; 20(6):9759-9780. PubMed ID: 37322910
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
