Mental and neurological diseases such as schizophrenia, depression, and autism have high morbidity and rates of misdiagnosis, but their imaging features are unapparent. At present, there are no objective indicators for early diagnosis, risk assessment, and treatment options. One reason is that imaging analysis of these brain illness involves complex artificial intelligence analysis models and methods.
In this report, we will introduce 1) how to use MRI-based brain function and structure imaging information of diseases to characterize brain functional activity, static functional network, dynamic functional and structural network, thereby revealing the neuroimaging mechanism of these diseases; 2) how to use multimodal network-based artificial intelligence pattern recognition methods to discover imaging biomarkers of neuropsychiatric diseases, to improve the classification accuracy, and finally offering data-driven reliable indicators for clinical diagnosis and assessment.
Dr. Huafu Chen is a Professor in MOE Key Laboratory for Neuroinformation, Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China. He is a Changjiang distinguished professor, a recipient of the national science fund for distinguished young scholars, Elsevier China Highly Cited Scholar (2020/ 2021) and top 2% of the world's neuroscience scientists of China. Currently, he is a director of the Chinese Society of Image and Graphics, deputy director of the Organization Construction Committee and Visual Cognition and Computing Professional Committee, deputy director of MOE Key Lab for Neuroinformation at University of Electronic Science and Technology of China, as well as executive deputy director of High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province.
Dr. Huafu Chen focuses his research on developing artificial intelligence and machine learning methods for pattern recognition of magnetic resonance brain imaging data, uncovering neuroimaging mechanism of neurological and psychiatric diseases, detecting typical neuroimaging features of these diseases, and further providing imaging evidences for clinical diagnosis and assessment. Until now, he has leaded more than 20 scientific research projects: 4 key research projects including the National Natural Science Foundation of China and artificial intelligence 2030 research of the Ministry of Science and Technology, 863 and 973 projects and so on. As the corresponding author, he has published 300 papers in SCI journals such as PNAS, Science Advance, Nature Communications, Cell Reports, Molecular Psychiatry, Brain, Neurology, IEEE Transactions on Medical Imaging, etc., which have been cited more than 10,000 times by SCI papers, and won Sichuan Province scientific and technological progress first prize in natural Science category.
Title: Computational solutions to explore genomic 3D organization
In eukaryotes, chromatin folds into a complex three-dimensional structure that plays a critical role in gene expression, cell function, and biological development. Chromosome Conformation Capture (3C) based technologies, such as 3C, 4C, 5C, Hi-C, ChIA-PET and HiChIP, have characterized the architecture of 3D genome. However, limited by the expense and time cost of wet lab experiment, it is a great challenge to explore the chromosome contacts of unrecognized cell line or species. This talk will overview different technologies for 3D genome and present computational solutions to explore genomic 3D organization. This talk will also describe some of our recent work for calling targeted 3D chromatin loops, evaluating targeted chromatin conformation capture-specific methodologies, and a new database to provide all the curated pathological variants and genomic disruptions for mining the putative pathological effects of any genetic mutation.
Dr. Min Li is currently a Professor and the vice dean at the School of Computer Science and Engineering, Central South University, P. R. China. She is a recipient of the National Science Fund for Distinguished Young Scholars and Elsevier China Highly Cited Scholar (2020/ 2021). Currently, she is a director of the Hunan Provincial Engineering Research Center for Intelligent Computing in Biology and Medicine, and deputy director of the Hunan Provincial Key Lab on Bioinformatics. She is serving as the Editorial Board Member of Big Data Mining and Analytics, International Journal of Data Mining and Bioinformatics, International Journal of Bioinformatics Research and Applications, and Interdisciplinary Sciences: Computational Life Sciences. Her research interests include Algorithms for Computational Biology and Bioinformatics, mainly focus on algorithms and tools in de novo genome assembly, 3D genome, biological network analysis and protein bioinformatics, etc. She has published more than 100 technical papers in refereed journals such as Genome Biology, Genome Research, Nucleic Acids Research, Bioinformatics, IEEE/ACM Transactions on Computational Biology and Bioinformatics, and conference proceedings such as BIBM, GIW and ISBRA. According to Google scholar, her paper citations is more than 9000 and H-index is 49.