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School of Life Science and Technology

The School of Life Science and Technology (SLST) of Xidian University is committed to making significant improvements in current and future life science technologies through well-funded research and development. SLST was founded in 2009, merging two former research entities (i.e., the Department of Biomedical Engineering and the Research Center of Intelligent Biological Information affiliated with the School of Electronics Engineering) with most of their pioneering staff. The former has its long history back to 1990, with particular strength in bio-signal processing. The latter was founded in 2006, with special focus on cutting-edge life science technologies, such as neuroimaging and molecular imaging. Therefore, SLST inherits the two traditions.


Currently, SLST consists of three departments, i.e. the Department of Biomedical Engineering, the Department of Biotechnology and the Department of Intelligent Medical Engineering, with 56 faculty members, among whom 17 are professors, 21 associate professors and 18 lecturers. SLST has its reputation throughout the province and the nation, and has been supported by several prestigious programs implemented by the Ministry of Education, the National Natural Science Foundation, etc. Moreover, SLST has ample resources of funding from both governments and companies.



SLST provides bachelor’s, master’s and doctor’s programs for students, with no special requirements for the academic background of applicants.


Majors for undergraduates

1. Biomedical Engineering

2. Biotechnology

3. Intelligent Medical Engineering


Programs for master students

1. Biomedical Engineering

2. Biomaterials and Cellular Engineering


Programs for PhD students

Biological Information Science and Technology



SLST is research-oriented with the research fields spanning in three major directions. The detailed information is as follows:


1. Molecular Imaging Technology

The research of molecular imaging technology aims at developing highly sensitive and specific molecular imaging probes and novel multi-modal imaging systems, which can realize the qualitative and quantitative analysis of biological processes at the cellular and molecular level in vivo. With the development of molecular imaging probes and new imaging modalities, we could acquire comprehensive information on tumors' physiological and pathological properties from anatomical, functional, metabolic, and molecular perspectives. Further, we explore the applications of molecular imaging technology in early diagnosis and molecular classification of tumors, the location of tumor margin, and the evaluation of drug efficacy, and gain insights into the mechanism of tumor occurrence, development, metastasis, and induced apoptosis.


2. Neuroimaging and Engineering

The research of neuroimaging and engineering embraces the national strategic needs in life and health science and collaborates closely with top-level hospitals. The research of neuroimaging and engineering focuses on the pathogenic mechanism, early diagnosis, and intervention of major brain diseases. The pathogenic mechanism of brain diseases is revealed by analyzing the large-scale clinical imaging database using fMRI and EEG. We adopt acupuncture from the traditional Chinese medicine to treat brain diseases. We explore quantitative mechanism of acupuncture and further promote the application of intelligent acupuncture therapy.


3. Biomedical Big Data

The research of biomedical big data analytics primarily focuses on the standardized management of large-scale, multi-type, high-dimensional, and high-uncertainty biomedical databases, efficient parallel computing, correlation analysis between genomics and radiomics for major diseases, rapid screening of disease biomarkers, and targeted drug development. Also, we make research on constructing risk assessment and early-warning models with population-based cohorts, and provide accurate and comprehensive view on the diagnosis, treatment, and prevention of major diseases. By integrating computational biology and clinical data, we study intelligent computing methods to accurately predict the risk and prognosis for individual patients, which helps to deliver precise treatment of a given disease.




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