# positions[].organizations[].parent[].label
College of Education and Human Development

# positions[].organizations[].parent[].label
Texas A&M Engineering Experiment Station (TEES)

# overview
My main motivation is to unravel molecular mechanisms and to modulate emergent behavior of biomolecular networks with the development and application of computational tools (including molecular modeling, network simulation, optimization, machine learning, graph theory, and systems and control theory).  To that end, I aim at an iterative process that models and experiments can feed each other.

# keywords[]
3404 Medicinal And Biomolecular Chemistry

# keywords[]
3102 Bioinformatics And Computational Biology

# keywords[]
Networking And Information Technology R&d (nitrd)

# keywords[]
4007 Control Engineering, Mechatronics And Robotics

# keywords[]
3404 Medicinal And Biomolecular Chemistry

# keywords[]
Networking And Information Technology R&d (nitrd)

# keywords[]
4607 Graphics, Augmented Reality And Games

# keywords[]
Stem Cell Research - Nonembryonic - Human

# educationAndTraining[].organization.label
Boston University - (Boston, Massachusetts, United States)

# educationAndTraining[].organization.label
Massachusetts Institute of Technology - (Cambridge, Massachusetts, United States)

# educationAndTraining[].organization.label
University of Science and Technology of China - (Hefei, China)

# awardsAndHonors[].label
Faculty Early Career Development (CAREER) Program

# publications[].label
Blind prediction of interfacial water positions in CAPRI.

# publications[].label
ESR1 ligand-binding domain mutations in hormone-resistant breast cancer.

# publications[].label
Predicting Molecular Interactions in Structural Proteomics

# publications[].label
Testing the substrate-envelope hypothesis with designed pairs of compounds.

# publications[].label
Multimodal Machine Learning for Protein Variant Effect Prediction and De Novo Design

# publications[].label
Docking with PIPER and refinement with SDU in rounds 6-11 of CAPRI.

# publications[].label
ClusPro: performance in CAPRI rounds 6-11 and the new server.

# publications[].label
Improved flexible refinement of protein docking in CAPRI rounds 22-27.

# publications[].label
SDU: A Semidefinite Programming-Based Underestimation Method for Stochastic Global Optimization in Protein Docking.

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
Protein docking by the underestimation of free energy funnels in the space of encounter complexes.

# publications[].label
Overcoming mutation-based resistance to antiandrogens with rational drug design.

# publications[].label
Charge Optimization Theory for Induced-Fit Ligands.

# publications[].label
Achieving reliability and high accuracy in automated protein docking: ClusPro, PIPER, SDU, and stability analysis in CAPRI rounds 13-19.

# publications[].label
L2-GCN Layer-Wise and Learned Efficient Training of Graph Convolutional Networks

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
Crowdsourced mapping of unexplored target space of kinase inhibitors.

# publications[].label
Single cell RNA sequencing-based identification of molecular drivers in circulating tumor cell cluster formation and lung metastasis

# publications[].publisher
American Association for Cancer Research (AACR)

# publications[].label
Fold2Seq: A Joint Sequence(1D)-Fold(3D) Embedding-based Generative Model for Protein Design.

# publications[].label
Molecular mechanisms and design principles for promiscuous inhibitors to avoid drug resistance: lessons learned from HIV-1 protease inhibition.

# publications[].label
Noncoding variant effect prediction using genome sequence and chromatin structure

# publications[].label
Variant effect prediction using structure-informed protein language models

# researcherOn[].label
CCF: EAGER: Dimension Reduction and Optimization Methods for Flexible Refinement of Protein Docking

# researcherOn[].awardedBy.label
National Science Foundation - (Arlington, Virginia, United States)

# researcherOn[].label
Unraveling Molecular and System-Level Mechanisms of Human Disease-Associated Protein Mutations

# researcherOn[].awardedBy.label
National Institutes of Health - (Bethesda, Maryland, United States)

# researcherOn[].awardedBy.preferredLabel
DHHS-NIH-National Institute of General Medical Science

# researcherOn[].label
CAREER: Physics-Constrained Modeling of Molecular Texts, Graphs, and Images for Deciphering Protein-Protein Interactions

# researcherOn[].awardedBy.label
Directorate for Computer & Information Science & Engineering - (Arlington, Virginia, United States)

# streetAddress
Texas A&M University; Electrical Engineering; 3128 TAMU

# organizations[]
College of Education and Human Development

# organizations[]
Texas A&M Engineering Experiment Station (TEES)

# schools[]
Texas A&M Engineering Experiment Station (TEES)

# schools[]
College of Education and Human Development

# etdChairOf[].label
Zhou, Fangtong (2020-05). Identifying Nuclear Receptor Ligands through Sequence-Based Deep Learning. Master's Thesis.

# etdChairOf[].label
Sun, Yuanfei (2023-12). Protein Multimodal Learning for Variant Effect Prediction and Protein Engineering. Doctoral Dissertation.

# etdChairOf[].label
Cao, Yue (2021-12). Optimization, Learning and Generation for Proteins: Docking Structures and Mapping Sequence–Function Relationships. Doctoral Dissertation.

# etdChairOf[].label
Zhu, Shaowen (2019-08). DE NOVO PROTEIN DESIGN OF NOVEL FOLDS USING GUIDED CONDITIONAL WASSERSTEIN GENERATIVE ADVERSARIAL NETWORKS (GCWGAN). Master's Thesis.

# etdChairOf[].label
Tan, Wuwei (2023-08). Genetic Mutation Effect Prediction: Incorporating 1D Sequence and 3D Structure. Doctoral Dissertation.

# etdChairOf[].label
Yan, Yi (2018-05). Efficiency Prediction and Mechanism Discovery for the CRISPR-Cas9 System. Master's Thesis.

# etdChairOf[].label
Wu, Di (2018-12). Structured Sparsity Learning for Coevolution-Based Protein Contact Prediction. Master's Thesis.

# etdChairOf[].label
Chen, Haoran (2018-08). Improving Molecular-Level Protein Docking and Interpreting System-Level Cancer Mechanisms through Machine Learning. Master's Thesis.

# etdChairOf[].label
Karimi, Mostafa (2020-12). Circumventing Drug Resistance by Molecular Design: Exact Combinatorial Optimization and Deep Generative Models. Doctoral Dissertation.