Wanxiaogeng头像

Wanxiaogeng

Research direction: Time Series Causality, Complex Networks, Bioinformatics

Education:

10 Access

  • Email: wxgbj88@sina.com
  • Office : Wenli Building 316

Introduction

Xiaogeng Wan is currently a lecturer of the Mathematics Department in the School of Mathematics and Physics at Beijing University of Chemical Technology. He obtained his Ph.D. in Mathematics from Imperial College London in 2015 and worked as a postdoctoral researcher in the Department of Mathematical Sciences at Tsinghua University from 2015 to 2017. Her research focuses on bioinformatics, causal inference, complex systems and network theory, time series causal measures, information transfer, protein structure classification studies, biological sequence feature extraction and evolutionary classification analysis, feature selection algorithms, artificial intelligence, causal graph learning, geometrical and topological machine learning, molecular geometrical and topological modeling, mutual information and entropy estimators, biostatistics and computer vision in medical studies.


Education

Work Experience

Social Position

Social Activities

Research

Bioinformatics, causal inference, complex systems and network theory, time series causal measures, information transfer, protein structure classification studies, biological sequence feature extraction and evolutionary classification analysis, feature selection algorithms, artificial intelligence, causal graph learning, geometrical and topological machine learning, molecular geometrical and topological modeling, mutual information and entropy estimators, biostatistics and computer vision in medical studies.


Teaching

Probability Theory and Mathematical Statistics, Specialty English in Mathematics


Postgraduates

Funding

Vertical Project

Horizontal Project

Publications

1. Wan X*, Tan X, A protein structural study based on the centrality analysis of protein sequence feature networks, PLOS ONE,

2021, PLoS ONE 16(3): e0248861.
2. Qi T, Wan X*, A Protein Structural Study Based on Sequence Feature Networks. Chinese Journal of Bioinformatics, 2021.
3. Wan X*, Tan X, A simple protein evolutionary classification method based on the mutual relations between protein
sequences, Current Bioinformatics, 2020, 15(10): 1123-1139.
4. Tian K, Zhao X, Wan X, Yau ST*, Amino acid torsion angles enable prediction of protein fold classification, Scientific Reports,
2020, 10: 21773.
5. Wan X*, Tan X, A study on separation of the protein structural types in amino acid sequence feature spaces, PLOS ONE,
2019, 14(12): e0226768.
6. Razak FA, Wan X, Jensen HJ*, Information theoretic measures of causality: music performance as a case study, Handbook
of research methods in complexity science, theory and applications, Edward Elgar Publishing, 2018, 45-53.
7. Wan X*, Xu L, A study for multiscale information transfer measures based on conditional mutual information, PLOS ONE,
2018,13(12): e0208423.
8. Wan X, Zhao X, Yau ST*, An information-based network approach for protein classification, PLOS ONE, 2017, 12(3):
e0174386.
9. Wan X, Cruts B, Jensen HJ, The causal inference of cortical neural networks during music improvisations,PLOS ONE,
2014,9(12): e112776.
10. Zhao X, Wan X, He RL,Yau ST, A new method for studying the evolutionary origin of the SAR11 clade marine bacteria,
Molecular Phylogenetics & Evolution, 2016,98:271-279.
11. Wan X*, Protein structural type prediction based on the torsion angle preference of K-mers, 2021, 19(1): 1-12.


Awards

Patent

Honor Reward

Admissions Information