Software Web: A self-knowledge distillation-driven CNN-LSTM model for predicting disease outcomes using longitudinal microbiome data
Software Web: scGMM-VGAE: A Gaussian mixture model-based variational graph autoencoder algorithm for clustering single-cell RNA-seq data
Software Web: ABT-MPNN: an atom-bond transformer-based message-passing neural network for molecular property prediction
Software Web Deep learning-based MRI-genomic mapping
Software Web: Molecular Property Prediction based on Bimodal Supervised Contrast Learning
Software Web: Machine Learning Model trained on a High-Throughput Antibacterial Screen
Software Web: Multiomics-based deep tensor survival model for time-to-event prediction
Software Web: Self-supervised deep learning models for CT image segmentation
Software Web: Semi-Supervised Deep Generative Models for Image Segmentation
Software Web: A re-trainable deep learning tool for single cell RNA-sequencing based cell type labeling
Software Web: Deep learning-driven algorithm for clustering small molecules
Software Web: Sparse Matrix Profile DenseNet for COVID-19 Diagnosis
Software Web: Deep learning-driven algorithm for predicting drug mechanism of action
Software Web: Computational prediction of the pathogenic status of cancer-specific somatic variants
Software Web: Bayesian tensor factorization-drive breast cancer subtyping by integrating multi-omics data
Software Web: DTF: Deep tensor factorization for predicting anticancer drug synergy
Software Web: Matrix profile-guided attention LSTM model for forecasting COVID-19 cases
Software Web: An OpenMP based tool for finding LCS of DNA sequence data
Description: predict disease outcomes using longitudinal microbiome data.
Citation: Fung et al. 2023, Bioinformatics Advances
Description: A clustering framework to combine traditional statistical modeling and deep leaning algorithm.
Citation: Lin et al. 2023, Machine Learning: Science and Technology
Description: An atom-bond transformer-based message-passing neural network (ABT-MPNN), to improve the molecular representation embedding process 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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