iGEM@XJTLU
International Genetically Engineered Machine Competition
XJTLU iGEM Team
The iGEM (International Genetically Engineered Machine) Competition is a premier annual international competition in synthetic biology. It covers interdisciplinary fields ranging from life sciences to mathematics, chemistry, engineering, and big data. The competition aims to use synthetic biology and engineering approaches to address challenges in the environment, healthcare, and beyond. The XJTLU iGEM team has participated for many years and has repeatedly won gold medals with outstanding results. Since 2015, many team members have pursued advanced studies at top universities.
About the XJTLU iGEM Team
The XJTLU iGEM Team is Xi'an Jiaotong-Liverpool University (XJTLU)'s official team focused on the international academic competition in synthetic biology. Over the years, it has won multiple gold medals, silver medals, and track nominations. The iGEM project spans nine months. The XJTLU iGEM team typically begins forming in January–February each year, with participating students independently collaborating on experiments, modelling, fieldwork, and other research tasks. Their results are presented on the international stage through webpages and oral presentations in October–November each year. Established in 2015, the XJTLU iGEM team has a long history, with many alumni having gone on to pursue Master's or PhD degrees at worldrenowned institutions such as Harvard, Johns Hopkins, and Karolinska Institutet.
From 2024, the XJTLU iGEM team is divided into two tracks. XJTLU-CHINA, as a traditional experimental team with ten years of team history at SIP, is dedicated to solving problems in synthetic biology; applying technical means such as genetic engineering and molecular biology experiments to build mathematical models of living systems based on engineering thinking; designing and optimizing biological parts, biomaterials, and bio-detection systems. XJTLU-Software is a newly established software team in 2024, dedicated to solving the problems of computational modelling, simulation and data analysis involved in synthetic biology; applying popular computer algorithms such as Artificial Intelligence, Deep Learning, etc. to build AI-based predictive models, designing data analysis and visualisation tools, etc., and providing brand new computational solutions for synthetic biology and iGEM community.