Leyi Wei
Orcid: 0000-0003-1444-190X
According to our database1,
Leyi Wei
authored at least 87 papers
between 2014 and 2024.
Collaborative distances:
Collaborative distances:
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Bibliography
2024
Inf. Sci., March, 2024
Inter- and intra-uncertainty based feature aggregation model for semi-supervised histopathology image segmentation.
Expert Syst. Appl., March, 2024
NanoCon: contrastive learning-based deep hybrid network for nanopore methylation detection.
Bioinform., February, 2024
StructuralDPPIV: a novel deep learning model based on atom structure for predicting dipeptidyl peptidase-IV inhibitory peptides.
Bioinform., February, 2024
J. Chem. Inf. Model., January, 2024
MucLiPred: Multi-Level Contrastive Learning for Predicting Nucleic Acid Binding Residues of Proteins.
J. Chem. Inf. Model., 2024
CACPP: A Contrastive Learning-Based Siamese Network to Identify Anticancer Peptides Based on Sequence Only.
J. Chem. Inf. Model., 2024
AttenSyn: An Attention-Based Deep Graph Neural Network for Anticancer Synergistic Drug Combination Prediction.
J. Chem. Inf. Model., 2024
J. Chem. Inf. Model., 2024
2023
Quant. Biol., December, 2023
ConPep: Prediction of peptide contact maps with pre-trained biological language model and multi-view feature extracting strategy.
Comput. Biol. Medicine, December, 2023
MolCAP: Molecular Chemical reActivity Pretraining and prompted-finetuning enhanced molecular representation learning.
Comput. Biol. Medicine, December, 2023
DeepProSite: structure-aware protein binding site prediction using ESMFold and pretrained language model.
Bioinform., December, 2023
A general hypergraph learning algorithm for drug multi-task predictions in micro-to-macro biomedical networks.
PLoS Comput. Biol., November, 2023
MolFPG: Multi-level fingerprint-based Graph Transformer for accurate and robust drug toxicity prediction.
Comput. Biol. Medicine, September, 2023
Rm-LR: A long-range-based deep learning model for predicting multiple types of RNA modifications.
Comput. Biol. Medicine, September, 2023
PLPMpro: Enhancing promoter sequence prediction with prompt-learning based pre-trained language model.
Comput. Biol. Medicine, September, 2023
Comput. Biol. Medicine, July, 2023
MPI-VGAE: protein-metabolite enzymatic reaction link learning by variational graph autoencoders.
Briefings Bioinform., July, 2023
ExamPle: explainable deep learning framework for the prediction of plant small secreted peptides.
Bioinform., March, 2023
SiameseCPP: a sequence-based Siamese network to predict cell-penetrating peptides by contrastive learning.
Briefings Bioinform., January, 2023
AFP-MFL: accurate identification of antifungal peptides using multi-view feature learning.
Briefings Bioinform., January, 2023
Multi-modality Contrastive Learning for Sarcopenia Screening from Hip X-rays and Clinical Information.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023
Shape-aware contrastive deep supervision for esophageal tumor segmentation from CT scans.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023
2022
A multi-label learning model for predicting drug-induced pathology in multi-organ based on toxicogenomics data.
PLoS Comput. Biol., September, 2022
Robust Feature Matching for Remote Sensing Image Registration via Guided Hyperplane Fitting.
IEEE Trans. Geosci. Remote. Sens., 2022
PESA-Net: Permutation-Equivariant Split Attention Network for correspondence learning.
Inf. Fusion, 2022
Recent Advances in the Prediction of Subcellular Localization of Proteins and Related Topics.
Frontiers Bioinform., 2022
EOCSA: Predicting prognosis of Epithelial ovarian cancer with whole slide histopathological images.
Expert Syst. Appl., 2022
Multi-view deep learning based molecule design and structural optimization accelerates the SARS-CoV-2 inhibitor discovery.
CoRR, 2022
MSMG-Net: Multi-scale Multi-grained Supervised Metworks for Multi-task Image Manipulation Detection and Localization.
CoRR, 2022
MechRetro is a chemical-mechanism-driven graph learning framework for interpretable retrosynthesis prediction and pathway planning.
CoRR, 2022
Deep convolutional neural networks with ensemble learning and transfer learning for automated detection of gastrointestinal diseases.
Comput. Biol. Medicine, 2022
GSAML-DTA: An interpretable drug-target binding affinity prediction model based on graph neural networks with self-attention mechanism and mutual information.
Comput. Biol. Medicine, 2022
ToxIBTL: prediction of peptide toxicity based on information bottleneck and transfer learning.
Bioinform., 2022
Bioinform., 2022
StackTADB: a stacking-based ensemble learning model for predicting the boundaries of topologically associating domains (TADs) accurately in fruit flies.
Briefings Bioinform., 2022
Distant metastasis identification based on optimized graph representation of gene interaction patterns.
Briefings Bioinform., 2022
SRDFM: Siamese Response Deep Factorization Machine to improve anti-cancer drug recommendation.
Briefings Bioinform., 2022
Briefings Bioinform., 2022
Semi-supervised Histological Image Segmentation via Hierarchical Consistency Enforcement.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022
2021
Protein subcellular localization based on deep image features and criterion learning strategy.
Briefings Bioinform., July, 2021
Identification of glioblastoma molecular subtype and prognosis based on deep MRI features.
Knowl. Based Syst., 2021
Domain adaptation based self-correction model for COVID-19 infection segmentation in CT images.
Expert Syst. Appl., 2021
BMC Bioinform., 2021
iDNA-ABT: advanced deep learning model for detecting DNA methylation with adaptive features and transductive information maximization.
Bioinform., 2021
Learning embedding features based on multisense-scaled attention architecture to improve the predictive performance of anticancer peptides.
Bioinform., 2021
ATSE: a peptide toxicity predictor by exploiting structural and evolutionary information based on graph neural network and attention mechanism.
Briefings Bioinform., 2021
Computational prediction and interpretation of cell-specific replication origin sites from multiple eukaryotes by exploiting stacking framework.
Briefings Bioinform., 2021
Predicting drug-induced hepatotoxicity based on biological feature maps and diverse classification strategies.
Briefings Bioinform., 2021
Classification and gene selection of triple-negative breast cancer subtype embedding gene connectivity matrix in deep neural network.
Briefings Bioinform., 2021
Briefings Bioinform., 2021
Iterative feature representation algorithm to improve the predictive performance of N7-methylguanosine sites.
Briefings Bioinform., 2021
PSSP-MVIRT: peptide secondary structure prediction based on a multi-view deep learning architecture.
Briefings Bioinform., 2021
Integrative machine learning framework for the identification of cell-specific enhancers from the human genome.
Briefings Bioinform., 2021
IEEE Access Special Section Editorial: Feature Representation and Learning Methods With Applications in Large-Scale Biological Sequence Analysis.
IEEE Access, 2021
2020
Fusing convolutional neural network features with hand-crafted features for osteoporosis diagnoses.
Neurocomputing, 2020
Identification of expression signatures for non-small-cell lung carcinoma subtype classification.
Bioinform., 2020
Identifying enhancer-promoter interactions with neural network based on pre-trained DNA vectors and attention mechanism.
Bioinform., 2020
Comparative analysis and prediction of quorum-sensing peptides using feature representation learning and machine learning algorithms.
Briefings Bioinform., 2020
Meta-GDBP: a high-level stacked regression model to improve anticancer drug response prediction.
Briefings Bioinform., 2020
MinE-RFE: determine the optimal subset from RFE by minimizing the subset-accuracy-defined energy.
Briefings Bioinform., 2020
Empirical comparison and analysis of web-based cell-penetrating peptide prediction tools.
Briefings Bioinform., 2020
ACPred-Fuse: fusing multi-view information improves the prediction of anticancer peptides.
Briefings Bioinform., 2020
CPPred-FL: a sequence-based predictor for large-scale identification of cell-penetrating peptides by feature representation learning.
Briefings Bioinform., 2020
PRISMOID: a comprehensive 3D structure database for post-translational modifications and mutations with functional impact.
Briefings Bioinform., 2020
2019
Fast Prediction of Protein Methylation Sites Using a Sequence-Based Feature Selection Technique.
IEEE ACM Trans. Comput. Biol. Bioinform., 2019
Developing a Multi-Dose Computational Model for Drug-Induced Hepatotoxicity Prediction Based on Toxicogenomics Data.
IEEE ACM Trans. Comput. Biol. Bioinform., 2019
Knowl. Based Syst., 2019
Integration of deep feature representations and handcrafted features to improve the prediction of N<sup>6</sup>-methyladenosine sites.
Neurocomputing, 2019
PEPred-Suite: improved and robust prediction of therapeutic peptides using adaptive feature representation learning.
Bioinform., 2019
Bioinform., 2019
Exploring sequence-based features for the improved prediction of DNA N4-methylcytosine sites in multiple species.
Bioinform., 2019
mAHTPred: a sequence-based meta-predictor for improving the prediction of anti-hypertensive peptides using effective feature representation.
Bioinform., 2019
IEEE Access, 2019
Identification and Prediction of Key Nucleotide Sites Using Machine Learning in Bioinformatics: A Brief Overview.
Proceedings of the 2019 IEEE Intl Conf on Parallel & Distributed Processing with Applications, 2019
LncPred-IEL: A Long Non-coding RNA Prediction Method using Iterative Ensemble Learning.
Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019
2018
J. Parallel Distributed Comput., 2018
RA-UNet: A hybrid deep attention-aware network to extract liver and tumor in CT scans.
CoRR, 2018
ACPred-FL: a sequence-based predictor using effective feature representation to improve the prediction of anti-cancer peptides.
Bioinform., 2018
Proceedings of the 24th International Conference on Pattern Recognition, 2018
2017
Local-DPP: An improved DNA-binding protein prediction method by exploring local evolutionary information.
Inf. Sci., 2017
Improved prediction of protein-protein interactions using novel negative samples, features, and an ensemble classifier.
Artif. Intell. Medicine, 2017
Artif. Intell. Medicine, 2017
2016
Exploring local discriminative information from evolutionary profiles for cytokine-receptor interaction prediction.
Neurocomputing, 2016
mGOF-loc: A novel ensemble learning method for human protein subcellular localization prediction.
Neurocomputing, 2016
2014
Improved and Promising Identificationof Human MicroRNAs by Incorporatinga High-Quality Negative Set.
IEEE ACM Trans. Comput. Biol. Bioinform., 2014