Computational Systems Biology and Bioinformatics Lab


 
We are pursuing multi-faceted projects, either methodology or translationally oriented. These projects are currently supported by grants from the NIH and NSF (R01GM122845, R01AG057555, R21AG083302, and NSF2230354).

-         Projects on Methodology Development

  • Language modeling for biomedical text, social network, and biomolecules (DNAs, RNAs, and proteins)
  • Geometric deep learning for macromolecular structure analysis
  • Causal learning for conterfactual predictions and its application to precision medicine
  • Date efficiency machine learning (semi-supervised learning, meta-learning, etc.)
  • Uncertainty quantification for out-of-distribution predictions
  • Generative AI for phenotype-based inverse molecule design
  • Graph mining on signed multilayer multiplex network
  • Multi-objective reinforcement learning for drug design
  • Multi-scale modeling of drug-target binding/unbinding kinetics using Molecular Dynamics simulation and machine learning
  • End-to-end deep learning algorithms for predicting genome-scale drug-target interactions and drug phenotypic responses
  • Reconstruction of high-resoulation personalized drug-target interaction, drug response, and disease-gene association networks through integrating multiple omics data

-         Projects on Translational Sciences

  • Alzheimer's disease drug repurposing (in collaboration with Profs. Maria Figueiredo Pereira, Patrick Rockwell, and Peter Serrano at Hunter College, and Prof. Li Gan at Weill Cornell Medicine)
  • Anti-cancer drug discovery with the focus on understudied novel targets (in collaboration with Prof. Hui Li at UVA, and Prof. Stephen Burley at Rutgers University)
  • Aging rejuvenation target and biomarker discovery (in collaboration with Prof. Alicia Melendez at Queens College)
  • Opioid Use Disorder drug discovery (in collaboration with Prof. Wayne Harding at Hunter College)
  • Small molecule drug design targeting human microbiome (in collaboration with Prof. Philip Bourne at UVA)
  • Discovery and development of annti-virulence therapies to combat pathogen drug resistance (in collaboration with Prof. Fiona Brinkman at SFU and Prof. David Perlin at Rutgers University)
  • AI-powered Physiologically Based Pharmacokinetics (PBPK) modeling (in collaboration with Prof. Junmei Wang at University of Pittsburgh)