Projects per year
Personal profile
Personal profile
Dr. Guangyu Wang is an Assistant Professor of Cardiovascular Sciences at Houston Methodist Research Institute (HMRI), Weill Cornell Medical College. He started his research group in July of 2021. The overarching goal of his research is to utilize high-throughput multi-omics datasets, mostly based on DNA and RNA sequencing, to develop models that explain how cell state is regulated. He is especially interested in endothelial cells (ECs), covering various aspects of their biology, such as their differentiation and transdifferentiation, and the stability/plasticity of their chromatin structure and histone modification.
Research interests
The broad goals of the research in the Wang lab are to understand:
- How epigenetics regulates transcriptome
- How transcriptional shifts affect cell states and cell/tissue level phenotypes
To achieve our goal, we are motivated by modulating the causes of transcriptional shifts and the translational potential of identifying. We develop and apply computational tools to integrate and interpret large biomedical and molecular datasets that can uncover the regulation mechanism and the effects of the transcriptional process.
Specifically, we aim to utilize high-throughput multi-omics datasets, mostly based on DNA and RNA sequencing, to develop models that explain how cell state is regulated. We are especially interested in endothelial cells (ECs), covering various aspects of their biology, such as their differentiation and trans-differentiation, and the stability/plasticity of their chromatin structure and histone modification.
Single-cell dynamics
Single-cell transcriptomics (scRNA-seq) and single-cell epigenomics (scATAC-seq) data revolutionize the field of regulatory genomics. We combine cutting-edge computational approaches with state-of-the-art single-cell profiling to better understand cell state transitions, decode cis-regulatory programs, and predict the effect of TF perturbations in single-cell datasets and their effect on cell identity in contexts such as cell trans-differentiation and reprogramming.
Chromatin structure & Histone modification:
The Wang lab seeks to understand the chromatin folding of genomic DNA, which is one of the most basic and important genomic regulations in dynamic processes such as differentiation or cellular state switching. We have developed computational methods to investigate cell identity-associated TADs (topological associated domains), stripes, and loops. We initially detected split and merging of TADs comparing fibroblast to ECs and suggested these TAD splitting and merging may play important role in cell differentiation and are highly associated with histone modification alternation (Wang et al, Genome Biology, 2020). We also developed computational methods that decipher open chromatin, histone modification, and transcription factor binding genome-wide in sub-populations of cells undergoing dynamic processes such as differentiation or stochastic state switching (Wang et al, Nature Communication, 2020; Wang et al, GPB, 2021).
AI & Machine learning
Data-driven research in Wang lab is powered by artificial intelligence (AI) and machine learning that guide us to understand more about biological systems and processes. We are currently working on:
- Deep learning for transcriptome to predict cell state transition and pseudo-time based on the RNA velocity model.
- Transferring learning for scRNA-seq and scATAC-seq to predict therapy choice and patient outcome.
- Web-based workflows of single-cell multi-omics to efficiently implement data preparation, advanced analysis, and integrative analysis of scRNA-seq and scATAC-seq.
External positions
Assistant Professor, Weill Cornell Medical College
2022 → …
Research Area Keywords
- Heart & Vascular
- Systems Medicine & Bioinformatics
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Collaborations and top research areas from the last five years
Projects
- 1 Active
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Landscapes for Cell State Transition Leveraging by Single-Cell Multi-Omics
9/1/23 → 8/31/28
Project: Federal Funding Agencies
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TADsplimer reveals splits and mergers of topologically associating domains for epigenetic regulation of transcription
Wang, G., Meng, Q., Xia, B., Zhang, S., Lv, J., Zhao, D., Li, Y., Wang, X., Zhang, L., Cooke, J. P., Cao, Q. & Chen, K., Apr 2 2020, In: Genome Biology. 21, 1, 84.Research output: Contribution to journal › Article › peer-review
Open Access4 Scopus citations -
MACMIC Reveals A Dual Role of CTCF in Epigenetic Regulation of Cell Identity Genes
Wang, G., Xia, B., Zhou, M., Lv, J., Zhao, D., Li, Y., Bu, Y., Wang, X., Cooke, J. P., Cao, Q., Lee, M. G., Zhang, L. & Chen, K., Feb 2021, In: Genomics, Proteomics and Bioinformatics. 19, 1, p. 140-153 14 p.Research output: Contribution to journal › Article › peer-review
Open Access4 Scopus citations -
Characterization and identification of long non-coding RNAs based on feature relationship
Wang, G., Yin, H., Li, B., Yu, C., Wang, F., Xu, X., Cao, J., Bao, Y., Wang, L., Abbasi, A. A., Bajic, V. B., Ma, L. & Zhang, Z., Sep 1 2019, In: Bioinformatics. 35, 17, p. 2949-2956 8 p.Research output: Contribution to journal › Article › peer-review
Open Access69 Scopus citations -
Machine learning uncovers cell identity regulator by histone code
Xia, B., Zhao, D., Wang, G., Zhang, M., Lv, J., Tomoiaga, A. S., Li, Y., Wang, X., Meng, S., Cooke, J. P., Cao, Q., Zhang, L. & Chen, K., Jun 1 2020, In: Nature Communications. 11, 1, 2696.Research output: Contribution to journal › Article › peer-review
Open Access23 Scopus citations -
A Potential Role for MAGI-1 in the Bi-Directional Relationship Between Major Depressive Disorder and Cardiovascular Disease
Banerjee, P., Chau, K., Kotla, S., Davis, E. L., Turcios, E. B., Li, S., Pengzhi, Z., Wang, G., Kolluru, G. K., Jain, A., Cooke, J. P., Abe, J. & Le, N-T., Jul 3 2024, (E-pub ahead of print) In: Current Atherosclerosis Reports. 26, 9, p. 463-483 21 p.Research output: Contribution to journal › Review article › peer-review