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Welcome to Xi Zhang's Homepage!



Xi Zhang, PhD
Postdoctoral Research Fellow
Department of Computational Medicine and Bioinformatics
Medical School, University of Michigan
100 Washtenaw Avenue
Ann Arbor, MI 48109‐2218, USA
Tel: (734)‐773-2530
Email: xizha@umich.edu


Research Interests

Predict protein structure from cryo-EM density map and related field, Computational Biology, Bioinformatics, De Novo Protein structure prediction, Biophysics, Molecular Modeling, Deep Learning, Algorithm design.


In the last decade, theoretical and technological innovations have been made in the field of cryo-EM, such as single particle analysis and direct electron detection cameras. However, cryo-EM has still been limited to 3-4 Å resolution, and it is challenging to determine sub-2Å structures. Although multiple methods exist such as Flex-EM, RosettaCM2 and EMD-Ref, most of the approaches construct models by optimally refining configurations with density map, which is helpful in atomic model reproduction but cannot improve cryo-EM data resolution. Moreover, these methods are highly relied on the initial predicted conformation. Currently, Dr. Xi Zhang is dedicated to developing state-of-the-art algorithms for high-resolution protein structure De Novo prediction with/from cryo-EM density map. As shown in Figure 1, Dr. Zhang and cooperators develop CRI-TASSER (cryo-EM I-TASSER), a new pipeline integrating the information of cryo-EM density map into the powerful approach I-TASSER for protein structure determination under cryo-EM experimental data. The new approach starts with protein sequence and the corresponding cryo-EM density map, and predicts the 3D structure of the query sequence.

Figure 1. CRI-TASSER pipeline for de novo protein structure determination with inputs of query sequence (blue inset) and the corresponding cryo-EM density map (orange inset).

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