2023 3rd International Conference on Bioinformatics and Intelligent Computing (BIC 2023)


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Prof. Ying Xu, IEEE Fellow, University of Georgia, USA


Ying Xu has been the "Regents and Georgia Research Alliance Eminent Scholar" Chair of bioinformatics and computational biology and Professor in Biochemistry and Molecular Biology Department since 2003 and was the Founding Director of the Institute of Bioinformatics, the University of Georgia (UGA). He received his Ph.D. degree in theoretical computer science from the University of Colorado at Boulder in 1991. He started his bioinformatics career in 1993 when he joined Oak Ridge National Lab, where he worked for ten and half years. In 2003, he was recruited to the UGA to build the Institute of Bioinformatics.  His current research interests are in cancer bioinformatics and systems biology, particularly in cancer metabolism. He has over 300 publications, including five books, with total citations more than 18,000 and H-Index = 69; and has given over 250 invited/contributed talks at conferences, research organizations and universities.

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Assoc. Prof. Enrico Marsili, University of Nottnigham Ningbo, China


Enrico Marsili received his doctorate in Chemical Engineering from the University of Rome, Italy. He has been visiting scientist at Center for Biofilm Engineering, Bozeman, USA (2003-2004). After postdoctoral research at University of Minnesota, he took a Lecturer position at Dublin City University. In 2012, he joined the newly formed Singapore Centre for Environmental Life Sciences Engineering, Singapore, as Principal Scientist. In 2019, he moved to Nazarbayev University as Associate Professor in the Department of Chemical and Materials Engineering. Since 2022, he, he is Associate Professor in Green Chemicals and Energy at China Beacons Institute, University of Nottingham, Ningbo, China. His research interests include biofilm electrochemistry, development of antimicrobial and antibiofilm agents, and biosensors for clinical applications. To date, he has published 80 papers, which have received over 5000 citations.

Speech Title: Electrochemically active biofilms – principles, characterization and applications

Abstract: Biofilms comprise of microorganisms encased in self-produced extracellular polymeric matrix, which provide mechanical stability, resistance to antimicrobials, and favors adhesion to nearly any surfaces. When biofilms grow onto electrodes, they are termed electroactive biofilm (EABs). The microorganisms in EABs are also known as electricigens. EABs are capable of extracellular electron transfer (EET) to and from solid acceptor, through direct or mediated mechanism.  EABs are beneficial to wastewater treatment, contribute to biogeochemical processes and are responsible for microbially influenced corrosion (MIC). A thorough comprehension of the mechanism underlying EET is needed for biofilm management and to develop productive EABs for bioremediation, biomedical, and biosensing applications. The EET mechanisms are investigated through a combination of electrochemical techniques (e.g. chronoamperometry and potentiostatic electrochemical impedance spectroscopy) and microscopy techniques. Following early studies on strong electricigens like Geobacter sp. and Shewanella sp., recent research has shown that most prokaryotes (e.g., Pseudomonas aeruginosa, Bacillus subtilis, Acinetobacter baumannii) and even a few eukaryotes (e.g., Candida sp.) exhibit weak electricigens activity under specific conditions, thus extending the validity of electrochemical methods for biofilm analysis.

In our group, we develop electrochemical methods for characterization of early biofilms in the subsurface environment and in biomedical devices In this presentation, I will give a brief introduction to electrochemical biofilm characterization and show how electrochemical methods provide complementary information to classical techniques for biofilm analysis, especially for weak electricigens. I will then show recent applications of these methods to biomedical sensors and electrofermentation.


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Prof. Xi Xie, Sun Yat-sen University, China


Prof. Xi Xie is currently a full professor in the School of Electronics and Information Technology at Sun Yat-sen University, and is an adjunct professor in the First Affiliated Hospital of Sun Yat-sen University at the meantime. He graduated from Stanford University in USA with PhD degree on 2014, and then worked as a postdoc researcher in the Prof. Robert Langer’s lab at Massachusetts Institute of Technology. On 2016, he started his own research lab at Sun Yat-sen University. Prof. Xi Xie has been focusing on the fundamental research on micro/nano-system for biomedical applications. He has published 90 manuscripts. As corresponding author or first authors, 60 manuscripts have been published on journals including Nature Biomedical Engineering, Nature Nanotechnology, Nature Protocols, Nature Communications and et al. These works were highlighted by Nature series journals for 3 times. He is also applying for more than 20 patents at the meantime. These works have been highlighted three times by Nature series journals. He was awarded by “MIT Technology Reviews Innovators Under 35 China”, and won the “Outstanding Scientific Award of Chinese Institute of Electronics”, and the “Microsystems & Nanoengineering Summit 2019 Young Scientist Award”. He has applied for 38 patents, served as the editorial board member in two core journals including Life Science Instruments, and served as the academic members in three academic associations in China.

Speech Title: Minimally Invasive Devices for Biomedical Applications

Abstract:  Micro/nano system technology have greatly facilitated the development of bioinformatics research. In the field of bioelectronics and bioinformatics, researches have been greatly attracted by biological system modeling and disease predictions based on the understanding of intracellular protein dynamic expression. We have been focusing on the fundamental research on micro/nano-system for biomedical applications, trying to address the key issues on three levels, from the outside to the inside, in vitro – transdermal – and in vivo, aiming to overcome the key challenge of how to develop bio-safe technology to detect and regulate biological disease: 1) On the in vitro cellular level, we made breakthrough process on the development of nano-devices that could safely penetrate cell membrane, achieving regulation and sensing of the intracellular contents dynamically. 2) On the transdermal level, we systematically developed transdermal theranostic system, achieving precise and in situ detection and therapy of diseases. 3) On the in vivo level, we creatively develop bio-safe implantable theranostic system, achieving safe regulation and sensing of diseases in vivo. Our work holds great promise on facilitating the development of new tools for biomedical sensing detection and biomedical therapy, which would be critically important for the field of bioelectronics.



Prof. Linlin Shen, School of Computer Science, Shenzhen University, China


Prof. Linlin Shen is currently the “Pengcheng Scholar” Distinguished Professor at School of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China. He is also an Honorary professor at School of Computer Science, University of Nottingham, UK and Distinguished Visiting Scholar at University of Macao. He serves as the director of Computer Vision Institute, AI Research Center for Medical Image Analysis & Diagnosis and China-UK joint research lab for visual information processing. He also serves as the Co-Editor-in-Chief of the IET journal of Cognitive Computation and Systems. He received the BSc and MEng degrees from Shanghai JiaoTong University, Shanghai, China, and the Ph.D. degree from the University of Nottingham, Nottingham, U.K. He was a Research Fellow with the University of Nottingham, working on MRI brain image processing. His research interests include deep learning, facial analysis and medical image processing. Prof. Shen is listed as the Most Cited Chinese Researcher by Elsevier. He received the Most Cited Paper Award from the journal of Image and Vision Computing. His cell classification algorithms were the winners of the International Contest on Pattern Recognition Techniques for Indirect Immunofluorescence Images held by ICIP 2013 and ICPR 2016.