IEEE-ACM Transactions on Computational Biology and Bioinformatics

Papers
(The H4-Index of IEEE-ACM Transactions on Computational Biology and Bioinformatics is 39. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-11-01 to 2024-11-01.)
ArticleCitations
Deep Learning Enables Accurate Diagnosis of Novel Coronavirus (COVID-19) With CT Images484
XGBoost Model for Chronic Kidney Disease Diagnosis448
CNN-RNN Based Intelligent Recommendation for Online Medical Pre-Diagnosis Support307
EEG-Based Brain-Computer Interfaces (BCIs): A Survey of Recent Studies on Signal Sensing Technologies and Computational Intelligence Approaches and Their Applications189
D-UNet: A Dimension-Fusion U Shape Network for Chronic Stroke Lesion Segmentation119
Advanced Machine-Learning Methods for Brain-Computer Interfacing83
A Novel Negative-Transfer-Resistant Fuzzy Clustering Model With a Shared Cross-Domain Transfer Latent Space and its Application to Brain CT Image Segmentation75
Graph Convolutional Networks for Drug Response Prediction74
Plant Disease Detection Using Generated Leaves Based on DoubleGAN72
A Fast Linear Neighborhood Similarity-Based Network Link Inference Method to Predict MicroRNA-Disease Associations71
A New ECG Denoising Framework Using Generative Adversarial Network71
DeepDSC: A Deep Learning Method to Predict Drug Sensitivity of Cancer Cell Lines71
Deep Bidirectional Classification Model for COVID-19 Disease Infected Patients65
Subject-Independent Emotion Recognition of EEG Signals Based on Dynamic Empirical Convolutional Neural Network64
MatchMaker: A Deep Learning Framework for Drug Synergy Prediction64
Deep Learning for Automated Feature Discovery and Classification of Sleep Stages62
ResNet-SCDA-50 for Breast Abnormality Classification62
A Deep Learning Framework for Identifying Essential Proteins by Integrating Multiple Types of Biological Information61
Imbalanced Breast Cancer Classification Using Transfer Learning58
A Method of Information Protection for Collaborative Deep Learning under GAN Model Attack56
Drug-Target Interaction Prediction Using Multi-Head Self-Attention and Graph Attention Network54
Amino Acid Encoding Methods for Protein Sequences: A Comprehensive Review and Assessment54
LDICDL: LncRNA-Disease Association Identification Based on Collaborative Deep Learning52
ILDMSF: Inferring Associations Between Long Non-Coding RNA and Disease Based on Multi-Similarity Fusion50
A Global and Local Enhanced Residual U-Net for Accurate Retinal Vessel Segmentation50
Cross-Modality LGE-CMR Segmentation Using Image-to-Image Translation Based Data Augmentation48
MGRFE: Multilayer Recursive Feature Elimination Based on an Embedded Genetic Algorithm for Cancer Classification48
GEFA: Early Fusion Approach in Drug-Target Affinity Prediction48
Multi-Modal Classification for Human Breast Cancer Prognosis Prediction: Proposal of Deep-Learning Based Stacked Ensemble Model47
Predicting in-vitro Transcription Factor Binding Sites Using DNA Sequence + Shape47
iPhosH-PseAAC: Identify Phosphohistidine Sites in Proteins by Blending Statistical Moments and Position Relative Features According to the Chou's 5-Step Rule and General Pseudo Amino Acid Composition46
Prediction of FMN Binding Sites in Electron Transport Chains Based on 2-D CNN and PSSM Profiles46
Multi-View Mammographic Density Classification by Dilated and Attention-Guided Residual Learning46
A Comprehensive Review of Computational Methods For Drug-Drug Interaction Detection46
DMFLDA: A Deep Learning Framework for Predicting lncRNA–Disease Associations44
MRI Based Radiomics Approach With Deep Learning for Prediction of Vessel Invasion in Early-Stage Cervical Cancer41
iPhosS(Deep)-PseAAC: Identification of Phosphoserine Sites in Proteins Using Deep Learning on General Pseudo Amino Acid Compositions40
Designing Uncorrelated Address Constrain for DNA Storage by DMVO Algorithm40
IMCHGAN: Inductive Matrix Completion With Heterogeneous Graph Attention Networks for Drug-Target Interactions Prediction40
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