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MAGIGENE Playback Online | MAGIGENE × South China Normal University Series Academic Salon (Viroomics)


Release time:

2023-07-07

The rapid development of high-throughput sequencing technology and machine learning methods provides an opportunity for in-depth study of virology from an omics approach. Around the current high-throughput data in the field of viroomics, such as bacteriophages and eukaryotic viruses, a series of common methods and techniques of data mining and analysis have been developed, and these bioinformatics methods and techniques are mainly suitable for viroomics analysis based on the two strategies of macro genome or macro virus group. At the same time, in view of the current practical biological and clinical problems, the wide application of artificial intelligence methods in the field of bioinformatics, and the possible wide use of the next three generations of sequencing technology, viroomics data mining and analysis methods and technologies are also facing a number of problems and challenges.

Conference Review
Academic Salon Viroomics Roundtable Discussion

On June 30, 2023, the "MAGIGENE × South China Normal University Series Academic Salon (Viroomics)" jointly organized by MAGIGENE and South China Normal University was successfully concluded at MAGIGENE's Shenzhen headquarters.
This conference focuses on the research progress of the virus group-artificial intelligence-enabled virus group. It is honored to invite four well-known scholars (in no particular order), Professor Sun Yanni of City University of Hong Kong, Professor Ma Yingfei of Shenzhen Advanced Institute of Chinese Academy of Sciences, Professor Shi Mang of Sun Yat-sen University and Professor Zhu Huaiqiu of Peking University, to give special presentations. Professor Shu Wensheng, founder and chairman of Guangdong Meige Gene Technology Co., Ltd., Ltd., delivered an opening speech.
 

MAGIGENE will, as always, be committed to providing experts and scholars with better scientific research services and creating a broader academic exchange platform. We look forward to working with you to write a new chapter in scientific research!

 

Part1 Opening Speech

Professor Wengsheng Shu, Founder and Chairman of MAGIGENE

Professor Shu Wensheng of the School of Life Sciences of South China Normal University, founder and chairman of Guangdong Meige Gene Technology Co., Ltd., delivered an opening speech. Professor Shu Wensheng said that artificial intelligence has iterated from a specific fragment scene to a deeper and more diverse application scene, and has gradually penetrated into all aspects of our lives. He hopes that through this exchange, viroomics will be promoted to a wider and deeper field, and at the same time, it can also promote the research of artificial intelligence-enabled virology.

 

Part2 Special Guest Report
—— Application of Transformer models in characterizing mobile genetic elements (phages and plasmids)

Sun Yanni, Associate Professor, City University of Hong Kong

Report Summary:
 

Large language models have achieved remarkable success in various applications, such as ChatGPT. As the blueprint of life, genomes can also be modeled by language models. In this talk, I will discuss our efforts in applying language models to characterize mobile genetic elements, including phages and plasmids, in metagenomic data. Our research aims to demonstrate the potential of language models in genomics and their ability to analyze complex biological data.

 

-Phage Synthetic Biology and Phage Therapy

Researcher Ma Yingfei, Shenzhen Advanced Institute, Chinese Academy of Sciences

Report Summary:
 

Bacteriophages have important ecological functions and are the classic model organisms for molecular biology research, but the extreme diversity of phages in nature makes their knowledge extremely limited. In recent years, the research goal of designing and constructing engineered phage for the prevention and treatment of bacterial infection has been focused on the analysis of phage diversity and function, and the following work has been carried out: 1) the correlation between phage-bacteria-human health has been revealed; based on intestinal phage culture, the mechanism by which phage can coexist with host bacteria for a long time in the intestinal tract has been analyzed; 2) the clinical application of phage therapy has been successfully carried out; 3) The general phage genome reduction technology was developed, the essential functional gene elements of phage were identified, and the chassis phage was obtained. This series of work expands the current understanding of phage diversity and function, and lays the foundation for the research and application of engineering phage. In the future, it is proposed to further construct an efficient and safe engineering phage on this basis, and explore its path for the prevention and treatment of bacterial infection.

 

-- Using machine learning to explore RNA virus circles

Prof. Shi Mang, Sun Yat-sen University

Report Summary:
The global RNA virus species are rich and diverse, and the viral genome sequence is highly differentiated, and the identification of RNA virus is still very dependent on the sequence homology of known viruses, which leads to a lot of low homology of the virus "dark matter" has not been found. This study developed a deep learning model based on sequence and structural information, namely LucaProt, and based on this method, 10,487 macro transcriptome in habitats around the world were mined for RNA viruses, which greatly expanded the diversity of RNA viruses in the world. On this basis, the evolutionary history and ecological characteristics of these viruses were studied in depth, thus refreshing people's understanding of RNA "virus circle" in all directions.
-- Some Problems of Viroomics Data Analysis and AI Technology

Professor Zhu Huaiqiu of Peking University

Report Summary:
The rapid development of high-throughput sequencing technology and machine learning methods provides an opportunity for in-depth study of virology from an omics approach. Around the current high-throughput data in the field of viroomics, such as bacteriophages and eukaryotic viruses, a series of common methods and techniques of data mining and analysis have been developed, and these bioinformatics methods and techniques are mainly suitable for viroomics analysis based on the two strategies of macro genome or macro virus group. At the same time, in view of the current practical biological and clinical problems, the wide application of artificial intelligence methods in the field of bioinformatics, and the possible wide use of the next three generations of sequencing technology, viroomics data mining and analysis methods and technologies are also facing a number of problems and challenges.
 

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