Research

Current Research Projects

Our group studies biological interaction networks and pathways in health and disease.

Our current research is grouped into three main projects:

1. Construction and analysis of cell-cell interaction networks and pathways in the human lung.

2. Chromatin interaction hubs and their dynamics in human cells (especially, endothelial cells).

3. Generation and maintenance of Bioinformatics data repositories, data analysis tools, and web platforms, for different types of interactions, networks, biological pathways, and disease mechanisms.

Papers and Posters

2023

[1] Lee, C., et al. (2023), "VEGF-B prevents excessive angiogenesis by inhibiting FGF2/FGFR1 pathway", Signal Transduction and Targeted Therapy [html]

[2] Xie Z., et al. (2023), "A comparison of cell-cell interaction prediction tools based on scRNA-seq data", Biomolecules [html]

[3] Zhang J., et al. (2023), "PDGFD-induced immunoproteasome activation and cell-cell interactions", Computational and Structural Biotechnology Journal [html]

2022

[1] Huang X., et al. (2022), "GSA Central: A web platform to perform, learn, and discuss Gene Set Analysis", Frontiers in Medicine [html]

[2] Lu W., et al. (2022), "PDGFD switches on stem cell endothelial commitment", Angiogenesis [html]

[3] Mora A., et al. (2022), "Chromatin Hubs: A biological and computational outlook", Computational and Structural Biotechnology Journal [html]

2021

[1] Xie B., et al. (2021), "Automatic cell type identification methods for single-cell RNA sequencing", Computational and Structural Biotechnology Journal [html]

[2] Xie C., et al. (2021), "Popularity and performance of bioinformatics software: the case of gene set analysis", BMC Bioinformatics [html]

2020

[1] Xie C., et al. (2020), "Popularity and performance of bioinformatics software -The case of gene set analysis", ISMB-LA Conference (Intelligent Systems in Molecular Biology - Latinamerica) 2020, , Mexico, [pdf]

2019

[1] Mei S., et al. (2019), "GREG -Studying transcriptional regulation using integrative graph databases", Database [html]

[2] Mora A. (2019), "Gene Set Analysis methods for the functional interpretation of non-mRNA data --Genomic range and ncRNA data", Briefings in Bioinformatics [html]

2018

[1] Mei S., et al. (2018), Studying transcriptional regulation using graph databases, Guangzhou International Conference on Stem Cell Biology 2018, , Guangzhou, China [pdf]