STAB
Spatio-Temporal cell Atlas of the human Brain
实验室简介
Biomed AI Lab focuses on the cross research of artificial intelligence and biomedicine. The team members come from different disciplines such as computer, mathematics, biology and physics. Based on multimodal biomedical big data, the laboratory develops and applies artificial intelligence algorithm theory and technology for health risk prediction, intelligent diagnosis, treatment and intervention, prognosis evaluation, etc. In recent years, focusing on the characteristics of biomedical big data, a series of artificial intelligence algorithms have been developed, which have been successfully applied to brain-gut axis, brain development, brain diseases and other scenes. Relevant work has been published in Nature, Science, Cell, Cell Metabolism, IEEE TPAMI, Molecular Psychology, Nature Communications and other journals. And has won the first prize of Wu Wenjun Artificial Intelligence Natural Science Award and the second prize of Natural Science of the Ministry of Education. The group has undertaken National Key Research and Development Plan Projects, key and general projects of National Natural Science Foundation of China, and sub projects of Major Science and Technology Projects in Shanghai,etc.
Biomedical artificial intelligence laboratory is a united and progressive scientific research team. Interested candidates can send their resumes to Professor Xing-Ming Zhao. Look forward to your joining!
研究方向
Based on the genomics, transcriptomics and metabolomics data produced by the lab and the public data platforms as well as the long- and short-read sequencing data, we aim to develop algorithms to identify the genetic risk genes and variants of brain diseases in Chinese population, explore the new pathogenesis of brain diseases based on multi-omics data, develop algorithm for molecular diagnosis, and study new diagnosis and treatment methods using big data.
Based on brain fMRI data, genomics data, electronic medical records, behavior data, environmental factors and other data types produced by the lab and global public databases, we will develop integrative methods based on imaging, molecule and behavior data using machine learning and deep learning models, identify the risk factors of brain diseases, and aim to provide intelligent diagnosis for brain diseases.
Based on the microbiome data, metabolomics data and MRI data produced by the lab and public data platforms, we carry out studies on the data analysis and algorithm development of metagenomics data by integrating long- and short-read sequencing data, microbial species identification and gene function analysis, virus-bacteria interaction prediction, association analysis between microbiome data and imaging, behavior and genomics data.
祝贺实验室论文"Characterizing schizophrenia-relevant structural variants and tandem repeats through long-read sequencing"被Science Bulletin录用!
祝贺赵兴明教授当选为国际计算生物学学会中国理事会(ISCB-China )副主席
2025年10月23日,北欧中心成立30周年庆典期间,生物医学人工智能实验室联合芬兰坦佩雷大学共同举办了《Sino-Nordic Workshop on Biomedical Signal Synthesis and Restoration -- Seeking lmproved Computer-Aided Diagnosis》(《生物医学信号合成与重建——人工智能辅助诊断》)专题研讨会。
祝贺实验室论文"A review of computational approaches for metagenomics by long-read sequencing"被SCIENCE CHINA Life Sciences录用!
2025年3月31日,实验室相关成果以《Metagenomic analysis characterizes stage-specific gut microbiota in Alzheimer's disease》为题,正式发表在Nature旗下精神病学领域高水平期刊Molecular Psychiatry。
College of Biomedical Engineering, Fudan University. (Room 1410, Building D2, Bay Valley Science and Technology Park, Yangpu District, Shanghai)
Telephone:86-21-55665546
Email:xmzhao AT fudan.edu.cn© Copyright 复旦大学生物医学人工智能实验室 版权所有