Hilal Tayara
Orcid: 0000-0001-5678-3479
According to our database1,
Hilal Tayara
authored at least 48 papers
between 2016 and 2024.
Collaborative distances:
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Bibliography
2024
PUResNetV2.0: a deep learning model leveraging sparse representation for improved ligand binding site prediction.
J. Cheminformatics, December, 2024
Enhanced prediction of hemolytic activity in antimicrobial peptides using deep learning-based sequence analysis.
BMC Bioinform., December, 2024
Generative AI in the Advancement of Viral Therapeutics for Predicting and Targeting Immune-Evasive SARS-CoV-2 Mutations.
IEEE J. Biomed. Health Informatics, November, 2024
Unlocking the therapeutic potential of drug combinations through synergy prediction using graph transformer networks.
Comput. Biol. Medicine, March, 2024
DL-SPhos: Prediction of serine phosphorylation sites using transformer language model.
Comput. Biol. Medicine, February, 2024
IF-AIP: A machine learning method for the identification of anti-inflammatory peptides using multi-feature fusion strategy.
Comput. Biol. Medicine, January, 2024
Advancing Peptide-Based Cancer Therapy with AI: In-Depth Analysis of State-of-the-Art AI Models.
J. Chem. Inf. Model., 2024
J. Chem. Inf. Model., 2024
AMPred-CNN: Ames mutagenicity prediction model based on convolutional neural networks.
Comput. Biol. Medicine, 2024
FvFold: A model to predict antibody Fv structure using protein language model with residual network and Rosetta minimization.
Comput. Biol. Medicine, 2024
Stacking based ensemble learning framework for identification of nitrotyrosine sites.
Comput. Biol. Medicine, 2024
A graph neural network approach for predicting drug susceptibility in the human microbiome.
Comput. Biol. Medicine, 2024
NaII-Pred: An ensemble-learning framework for the identification and interpretation of sodium ion inhibitors by fusing multiple feature representation.
Comput. Biol. Medicine, 2024
Stack-AAgP: Computational prediction and interpretation of anti-angiogenic peptides using a meta-learning framework.
Comput. Biol. Medicine, 2024
Comput. Biol. Medicine, 2024
SB-Net: Synergizing CNN and LSTM networks for uncovering retrosynthetic pathways in organic synthesis.
Comput. Biol. Chem., 2024
An integrative machine learning model for the identification of tumor T-cell antigens.
Biosyst., 2024
2023
J. Chem. Inf. Model., October, 2023
ORI-Explorer: a unified cell-specific tool for origin of replication sites prediction by feature fusion.
Bioinform., October, 2023
An ensemble of stacking classifiers for improved prediction of miRNA-mRNA interactions.
Comput. Biol. Medicine, September, 2023
iCpG-Pos: an accurate computational approach for identification of CpG sites using positional features on single-cell whole genome sequence data.
Bioinform., August, 2023
Artificial Intelligence in Drug Toxicity Prediction: Recent Advances, Challenges, and Future Perspectives.
J. Chem. Inf. Model., May, 2023
Briefings Bioinform., May, 2023
DL-m6A: Identification of N6-Methyladenosine Sites in Mammals Using Deep Learning Based on Different Encoding Schemes.
IEEE ACM Trans. Comput. Biol. Bioinform., 2023
2022
IEEE ACM Trans. Comput. Biol. Bioinform., 2022
ZayyuNet - A Unified Deep Learning Model for the Identification of Epigenetic Modifications Using Raw Genomic Sequences.
IEEE ACM Trans. Comput. Biol. Bioinform., 2022
Comput. Biol. Medicine, 2022
Bioinform., 2022
DeepCap-Kcr: accurate identification and investigation of protein lysine crotonylation sites based on capsule network.
Briefings Bioinform., 2022
Proceedings of the 13th International Conference on Information and Communication Technology Convergence, 2022
2021
Improved Predicting of The Sequence Specificities of RNA Binding Proteins by Deep Learning.
IEEE ACM Trans. Comput. Biol. Bioinform., 2021
PUResNet: prediction of protein-ligand binding sites using deep residual neural network.
J. Cheminformatics, 2021
Recent omics-based computational methods for COVID-19 drug discovery and repurposing.
Briefings Bioinform., 2021
RecSNO: Prediction of Protein S-Nitrosylation Sites Using a Recurrent Neural Network.
IEEE Access, 2021
Cr-Prom: A Convolutional Neural Network-Based Model for the Prediction of Rice Promoters.
IEEE Access, 2021
m6A-NeuralTool: Convolution Neural Tool for RNA N6-Methyladenosine Site Identification in Different Species.
IEEE Access, 2021
IEEE Access, 2021
2020
Comput. Biol. Chem., 2020
Identifying Enhancers and Their Strength by the Integration of Word Embedding and Convolution Neural Network.
IEEE Access, 2020
A CNN-Based RNA N6-Methyladenosine Site Predictor for Multiple Species Using Heterogeneous Features Representation.
IEEE Access, 2020
SpineNet-6mA: A Novel Deep Learning Tool for Predicting DNA N6-Methyladenine Sites in Genomes.
IEEE Access, 2020
2019
iIM-CNN: Intelligent Identifier of 6mA Sites on Different Species by Using Convolution Neural Network.
IEEE Access, 2019
4mCCNN: Identification of N4-Methylcytosine Sites in Prokaryotes Using Convolutional Neural Network.
IEEE Access, 2019
2018
Object Detection in Very High-Resolution Aerial Images Using One-Stage Densely Connected Feature Pyramid Network.
Sensors, 2018
Vehicle Detection and Counting in High-Resolution Aerial Images Using Convolutional Regression Neural Network.
IEEE Access, 2018
Deep Learning Models Based on Distributed Feature Representations for Alternative Splicing Prediction.
IEEE Access, 2018
2016
Sensors, 2016