Description: GraphBAN: An inductive graph-based approach for enhanced prediction of compound-protein interactions
Citation: Hadipour et al. 2025. Nature Communications
Description: CL-MFAP: A contrastive learning-based multimodal foundation model for molecular property prediction and antibiotic screening
Citation: Zhou et al. ICLR 2025
25: Software Web: An interpretable deep geometric learning model to predict the effects of mutations on protein–protein interactions using large-scale protein language model
24: Software Web: Conditional Probabilistic Diffusion Model Driven Synthetic Radiogenomic Applications
23: Software Web: Investigating Alignment-Free Machine Learning Methods for HIV-1 Subtype Classification
22: Software Web: A cross-cohort analysis of dental plaque microbiome in early childhood caries
21: Software Web: ST-CellSeg: Cell segmentation for imaging-based spatial transcriptomics using multiscale manifold learning
20. Software Web: iNGNN-DTI: prediction of drug – target interaction with interpretable nested graph geural network and pretrained molecule models
19. Software Web: Conditional Generative Adversarial Network Driven Radiomic Prediction of Mutation Status Based on Magnetic Resonance Imaging of Breast Cancer
18 .Software Web: A self-knowledge distillation-driven CNN-LSTM model for predicting disease outcomes using longitudinal microbiome data
17. Software Web: scGMM-VGAE: A Gaussian mixture model-based variational graph autoencoder algorithm for clustering single-cell RNA-seq data
16. Software Web: ABT-MPNN: an atom-bond transformer-based message-passing neural network for molecular property prediction
15. Software Web Deep learning-based MRI-genomic mapping
14. Software Web: Molecular Property Prediction based on Bimodal Supervised Contrast Learning
13. Software Web: Machine Learning Model trained on a High-Throughput Antibacterial Screen
12. Software Web: Multiomics-based deep tensor survival model for time-to-event prediction
11. Software Web: Self-supervised deep learning models for CT image segmentation
10. Software Web: Semi-Supervised Deep Generative Models for Image Segmentation
9. Software Web: A re-trainable deep learning tool for single cell RNA-sequencing based cell type labeling
8. Software Web: Deep learning-driven algorithm for clustering small molecules
7. Software Web: Sparse Matrix Profile DenseNet for COVID-19 Diagnosis
6. Software Web: Deep learning-driven algorithm for predicting drug mechanism of action
5. Software Web: Computational prediction of the pathogenic status of cancer-specific somatic variants
4. Software Web: Bayesian tensor factorization-drive breast cancer subtyping by integrating multi-omics data
3. Software Web: DTF: Deep tensor factorization for predicting anticancer drug synergy
2. Software Web: Matrix profile-guided attention LSTM model for forecasting COVID-19 cases
1. Software Web: An OpenMP based tool for finding LCS of DNA sequence data
Description: A deep learning model to evaluate the impact of mutations on PPIs
Citation: Zhang et al. 2025. Journal of Cheminformatics
Description: Diffusion model for synthetic image generation.
Citation: Chen et al. 2024. Plos Computational Biology
Description: Sequence based AI algorithm for HIV-1 subtype classification.
Citation: Wade et al. 2024. Bioinformatics Sciences
Description: Pipeline for meta-analysis of microbiome data.
Citation: Khan et al. 2024. iScience
Description: Manifold learning for cell segmentation
Citation: Li et al. 2024. Plos Computational Biology
Description: GNN for drug-target interaction prediction
Citation: Sun et al. 2024, Bioinformatics
Description: Generative AI for MRI imaging generation
Citation: Huang et al. 2024, Journal of Translational Medicine
Description: Longitudinal Microbiome data analysis
Citation: Fung et al. 2023. Bioinformatics Advances
Description: Clustering analysis of scRNA-seq data
Citation: Lin et al. 2023. Machine Learning: Science and Technology
Description: An atom-bond transformer for molecular property predictions.
Citation: Liu et al. 2022, Journal of Cheminformatics
Description Radiogenomic association of deep MR imaging features with genomic profiles and clinical characteristics in breast cancer.
Citation: Liu et al. 2023 Biomarker Research
Description: A bimodal supervised contrastive learning (BSCL) framework to integrate the SMILES string and the molecular graph in a unified network.to predict molecular property.
Citation: Sun et al. 2022, IEEE BIBM
Description: A Machine Learning Model trained on a High-Throughput Antibacterial Screen Increases the Hit Rate of Drug Discovery
Citation: Rahman, liu et al. 2022, Plos Computational Biology.
Description: Tightly integrated multiomics-based deep tensor survival model for time-to-event prediction
Citation: Zhang et al. 2022, Bioinformatics
Description: Self-supervised deep learning model for COVID-19 lung CT image segmentation highlighting putative causal relationship among age, underlying disease, and COVID-19
Citation: Fung et al. 2021, Journal of Translational Medicine
Description: Semi-Supervised COVID-19 CT Image Segmentation Using Deep Generative Models
Citation: Zammit et al. 2022, BMC Bioinformatics
Description: ChrNet: A re-trainable chromosome-based 1D convolutional neural network for predicting immune cell types
Citation: Jia et al. 2021, Genomics
Description: Deep clustering of small molecules at large-scale via variational autoencoder embedding and K-means Citation: Hadipour et al. 2022, BMC Bioinformatics
Description: A Two-dimensional Sparse Matrix Profile DenseNet for COVID-19 Diagnosis Using Chest CT Images
Citation: Liu et al. 2020, IEEE Access
Description: Deep learning-driven prediction of drug mechanism of action from large-scale chemical-genetic interaction profiles
Citation: Liu et al. 2022, Journal of Cheminformatics
Description: Computational prediction of the pathogenic status of cancer-specific somatic variants
Citation: Feizi et al. 2022, Frontiers in Genetics
Description: Bayesian tensor factorization-drive breast cancer subtyping by integrating multi-omics data
Citation: Liu et al. 2022, Journal of Biomedical Informatics
Description: A new algorithm integrating tensor factorization and deep learning to predict anticancer drug combinations
Citation: Sun et al. 2020, Bioinformatics
Description: A novel matrix profile-guided attention LSTM model for forecasting COVID-19 cases in USA
Citation: Liu et al. 2021, Frontiers in Public Health
Description: This repository contains three parallel implementation of the LCS algorithm in MPI, OpenMP, and hybrid MPI-OpenMP platforms.
Citation: Shikder et al. 2019, BMC Research Notes.
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