The Hu Lab
Health Data Science, Bioinformatics and Statistical Genetics
My research program focuses on developing and applying computational and statistical techniques for integrative analysis of big multimodal health data (omics data, imaging data, administrative and electronic medical records) for precision medicine. My group also collaborates very closely with local, national and international life science scientists and clinicians on different omics projects. Current PhD/MSc students' thesis projects are in the research areas: radiogenomics, medical imaging, rare disease diagnosis using facial photos and phenotypes, drug discovery, microbiome, single cell RNA sequencing and omics data integration.
Software Development and Resources
Software Tools Developed in The Hu Lab
Software Web: Multiomics-based deep tensor survival model for time-to-event prediction
Description: Tightly integrated multiomics-based deep tensor survival model for time-to-event prediction
Citation: Zhang et al. 2022, Bioinformatics
Software Web: Semi-Supervised Deep Generative Models for Image Segmentation
Description: Semi-Supervised COVID-19 CT Image Segmentation Using Deep Generative Models
Citation: Zammit et al. 2022, BMC Bioinformatics
Software Web: Deep learning-driven algorithm for clustering small molecules
Description: Deep clustering of small molecules at large-scale via variational autoencoder embedding and K-means
Citation: Hadipour et al. 2022, BMC Bioinformatics
Software Web: Deep learning-driven algorithm for predicting drug mechanism of action
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
Software Web: Computational prediction of the pathogenic status of cancer-specific somatic variants
Description: Computational prediction of the pathogenic status of cancer-specific somatic variants
Citation: Feizi et al. 2022, Frontiers in Genetics
Software Web: Bayesian tensor factorization-drive breast cancer subtyping by integrating multi-omics data
Description: Bayesian tensor factorization-drive breast cancer subtyping by integrating multi-omics data
Citation: Liu et al. 2022, Journal of Biomedical Informatics
Software Web: Matrix profile-guided attention LSTM model for forecasting COVID-19 cases
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
Software Web: Self-supervised deep learning models for CT image segmentation
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
Software Web: A re-trainable deep learning tool for single cell RNA-sequencing based cell type labeling
Description: ChrNet: A re-trainable chromosome-based 1D convolutional neural network for predicting immune cell types
Citation: Jia et al. 2021, Genomics
Software Web: Sparse Matrix Profile DenseNet for COVID-19 Diagnosis
Description: A Two-dimensional Sparse Matrix Profile DenseNet for COVID-19 Diagnosis Using Chest CT Images
Citation: Liu et al. 2020, IEEE Access
Software Web: DTF: Deep tensor factorization for predicting anticancer drug synergy
Description: A new algorithm integrating tensor factorization and deep learning to predict anticancer drug combinations
Citation: Sun et al. 2020, Bioinformatics
Software Web: An OpenMP based tool for finding LCS of DNA sequence data
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.
RecurrentCNV: A graph-based tool to recall recurrent copy number variations
Citations: Kanwar et al. 2015, International Journal of Cancer and Chi et al. 2016, Cancer Informatics.
Resources
Deep Learning
Data sets
Stanford Biomedical Network Dataset Collection
Human Pathology Proteome - The Human Protein Atlas
Genomics of Drug Sensitivity in Cancer
Deep Learning in Medicine and Biology: Data and Tools and here
cBioportal for Cancer Genomics
Pretrained Deep Learning Models for Bioinformatics
Deep Learning for Drug Discovery
Tools
Others
3rd Floor BMSB Card Access Request