Prof.Jing He

Issuing time:2021-09-18 07:25

何静.jpg

Name:

Jing He

Title:

Dr.

Affiliation:

University of Oxford

Email:

lotusjing@gmail.com

100-word   biography:

Dr. Jing He is with the University   of Oxford. Before relocating to UK, she was a Professor in the School of   Software and Electrical Engineering at Swinburne University of Technology,   Australia, from 2018-2021 and at Victoria University from 2008-2018. She was   awarded a Ph.D. degree from the Academy of Mathematics and System Science,   Chinese Academy of Sciences, in 2006 and used to work in University of   Chinese Academy of Sciences, China from 2006-2008. She has been active in areas   of Graph theory, Linear Programming, and some industry field such as   E-Health, Bioinformatics, Petroleum Exploration and Development, and Water   Resource Management. She has published over 200 research papers in refereed   international journals and conference proceedings, including Information   System, Information Sciences, IEEE Transaction on Knowledge and Data   Engineering (TKDE), Plos One, The Computer Journal, IJCAI, AAAI, ICDE, etc.   Dr. Jing He is an IEEE senior member, and her H-index is 24.

Title:

Graph isomorphism based   Structural Similarity Measurement and Its Applications with Covid-19 Genome   Sequencing

Abstract:

In   theoretical computer science, there is one unsolved problem in Optimisation:   if there is a strong polynomial-time solution for graph isomorphism. I have   been working on them for the past ten years and successfully proposed one   solution for the above-mentioned question. The proposed permutation and   equinumerosity based solution for subgraph isomorphism has been adopted to   work for new medicine discovery for anti-COVID 19.

As a structural biologist, I have   implemented and publish the RNA structure of the covid-19 and created a   resource library called 'Graph Map' on this basis. The resource library also   includes resources such as the evaluation of existing new coronavirus protein   structure models, which can help scientists better understand the covid-19   and promote the research and development of new coronary pneumonia drugs and   vaccines. Understanding the structure of the covid-19 structure is essential   for the development of new coronary pneumonia treatments and vaccines. I have   carefully analyzed the existing new coronavirus protein model and gave the   results to help the biomedical community. The structural model is based on   the graph isomorphism and subgraph isomorphism. Other scientists'   understanding of viral proteins is sometimes not so good. Therefore, it is   very important to verify important structures. In most cases, I only propose   minor corrections. But in some cases, corrections are of great significance.   Especially it is in the field of protein-ligand complexes, which is crucial   for follow-up research such as drug development.

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