Multi-model deep learning approach for segmentation of teeth and periapical lesions on pantomographs

N Adnan, F Umer, S Malik, OA Hussain - Oral surgery, oral medicine, oral …, 2024 - Elsevier
Introduction The fields of medicine and dentistry are beginning to integrate artificial
intelligence (AI) in diagnostics. This may reduce subjectivity and improve the accuracy of …

Deep learning prediction of steep and flat corneal curvature using fundus photography in post-COVID telemedicine era

JY Choi, H Kim, JK Kim, IS Lee, IH Ryu, JS Kim… - Medical & Biological …, 2024 - Springer
Recently, fundus photography (FP) is being increasingly used. Corneal curvature is an
essential factor in refractive errors and is associated with several pathological corneal …

[HTML][HTML] EnsembleDL-ATG: Identifying autophagy proteins by integrating their sequence and evolutionary information using an ensemble deep learning framework

L Yu, Y Zhang, L Xue, F Liu, R Jing, J Luo - Computational and Structural …, 2023 - Elsevier
Autophagy is a primary mechanism for maintaining cellular homeostasis. The synergistic
actions of autophagy-related (ATG) proteins strictly regulate the whole autophagic process …

DRANetSplicer: A Splice Site Prediction Model Based on Deep Residual Attention Networks

X Liu, H Zhang, Y Zeng, X Zhu, L Zhu, J Fu - Genes, 2024 - mdpi.com
The precise identification of splice sites is essential for unraveling the structure and function
of genes, constituting a pivotal step in the gene annotation process. In this study, we …

AdvanceSplice: Integrating N-gram one-hot encoding and ensemble modeling for enhanced accuracy

MR Rezvan, AG Sorkhi, J Pirgazi… - … Signal Processing and …, 2024 - Elsevier
Accurate splice site prediction is a critical challenge in genomics, essential for
understanding gene expression and disease-associated mutations. Splice sites mark the …

AtLASS: A Scheme for End-to-End Prediction of Splice Sites Using Attention-based Bi-LSTM

R Harada, K Kume, K Horie, T Nakayama… - IPSJ Transactions on …, 2023 - jstage.jst.go.jp
Eukaryotic genomes contain exons and introns, and it is necessary to accurately identify
exon-intron boundaries, ie, splice sites, to annotate genomes. To address this problem …

Sequential labelling and DNABERT For splice site prediction in Homo Sapiens DNA

MA Leksono, A Purwarianti - arXiv preprint arXiv:2212.07638, 2022 - arxiv.org
Genome sequencing technology has improved significantly in few last years and resulted in
abundance genetic data. Artificial intelligence has been employed to analyze genetic data in …

Splicescanner: An accurate and interpretable deep learning-based method for splice site prediction

R Wang, J Xu, X Huang, W Qi, Y Zhang - International Conference on …, 2023 - Springer
The identification of splice sites is significant to the delineation of gene structure and the
understanding of complicated alternative mechanisms underlying gene transcriptional …

Splam: a deep-learning-based splice site predictor that improves spliced alignments

KH Chao, A Mao, SL Salzberg, M Pertea - Genome biology, 2024 - Springer
The process of splicing messenger RNA to remove introns plays a central role in creating
genes and gene variants. We describe Splam, a novel method for predicting splice junctions …

Impact of U2-type introns on splice site prediction in Arabidopsis thaliana using deep learning

E Kabanga, S Yun, A Van Messem, W De Neve - bioRxiv, 2024 - biorxiv.org
In this study, we investigate the impact of introns on the effectiveness of splice site prediction
using deep learning models, focusing on Arabidopsis thaliana. We specifically utilize U2 …