Member Listing – Qian Cong

We mine large-scale data for biological discoveries

I am a computational biologist interested in mining large-scale data for biological insights. I focused on evolutionary genomics as a graduate student and worked on computational structural biology as a postdoctoral fellow. Leveraging on my expertise in genomics, evolution, and protein structure modeling, our lab works on using coevolution signals between proteins to predict protein-protein interaction (PPI) and model 3D structures of protein complexes on a proteome-wide scale. Our approach showed comparable performance to large-scale experimental screens in bacteria. Recent breakthroughs in modeling protein structures to atomic accuracy using deep learning methods (AlphaFold and RoseTTAFold) further empowered our PPI screen. In a recent project I co-led, we identified and modeled hundreds of Yeast protein complexes that provided functional insights into many biological processes. This advance was recognized as part of “the breakthrough of the year 2021” by Science. Despite the success of our methods in Yeast, their application to human proteins remain challenging. We are improving our PPI screen pipeline by enhancing the coevolution signals using draft genomes and developing dedicated methods for weaker interactions. Additionally, we are applying our methods and insights about proteins to systems of biomedical significance, such as cancer drivers and virulence factors.

protein-protein interaction, evolution, genomics, artificial intelligence, bioinformatics

2017