{"id":215,"date":"2023-12-23T08:34:37","date_gmt":"2023-12-23T08:34:37","guid":{"rendered":"https:\/\/fangbucks.com\/chenlab\/?page_id=215"},"modified":"2024-05-20T16:51:47","modified_gmt":"2024-05-20T16:51:47","slug":"about-us-en","status":"publish","type":"page","link":"https:\/\/fangbucks.com\/chenlab\/en\/about-us-en\/","title":{"rendered":"About us"},"content":{"rendered":"\t\t
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Principal investigator<\/h2>

Fang Chen, Associate Professor\u00a0<\/b>\u00a0<\/h4>
Fang graduated from the State Key Laboratory of Genetic Engineering at the Institute of Genetics, Fudan University<\/strong> in Shanghai, where he engaged in research related to medical molecular genetics during his doctoral studies. During his postdoctoral period at the College of Medicine, Pennsylvania State University<\/strong>, he conducted research in the cutting-edge fields of complex trait\/disease genomics, statistical genetics, and artificial intelligence in precision medicine. He participated in and led the large-scale study on tobacco and alcohol addiction in over three million individuals of diverse ethnic backgrounds under the GSCAN (GWAS & Sequencing Consortium of Alcohol and Nicotine use)<\/em><\/strong>, applying big data methods to deeply analyze the genetic landscape and diversity of tobacco and alcohol addiction. For the identification and functional analysis of key genes in complex traits\/diseases, he developed numerous new algorithms and open-source tools tailored to practical needs.<\/span><\/div>
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Fang’s related scientific achievements include more than 10 publications in international journals such as <\/span>Nature Genetics, Nature, Nature Communications, Genome Research, <\/em><\/strong>and<\/span> Molecular Psychiatry<\/em><\/strong>; one of his papers has been cited over 1200 times. He has delivered keynote speeches at top academic conferences in the industry, such as the <\/span>American Society of Human Genetics Annual Meeting (ASHG)<\/em><\/strong>, developed new methods and tools for genetic analysis applicable to samples of over three million individuals, and applied machine learning methods to disease target identification and drug development.<\/span><\/div>
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Fang’s series of pioneering studies have significant methodological innovation value and translational application prospects in elucidating the genetic mechanisms and diversity of complex traits\/diseases. These studies also promote the application of genomics and multi-omics data in new drug development and provide new ideas and methods for the development of precision medicine.<\/div>
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In addition, Fang has extensive experience in the industry. Before returning to China, he worked in Silicon Valley, USA, as a Sr. Data Engineer at Meta (formerly Facebook). Previously, Fang served as a Senior Bioinformatics Scientist at the well-known biotech company Sema4, where he was involved in the application research of large language models (LLMs)<\/strong> <\/em>in genomic data.<\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Education<\/strong><\/h4>

Sep. 2002- Jun. 2006\u00a0 \u00a0\u00a0 Sichuan University\u00a0 <\/span>Bachelor of Science (B.S.) Life Science<\/em><\/p>

Sep. 2006- Oct. 2012\u00a0 \u00a0 \u00a0Fudan University\u00a0 Doctor of Philosophy (Ph.D.) Medical & Molecular Genetics<\/em><\/p>

Work Experince\u00a0<\/strong><\/h4>

Nov. 2016- Nov. 2021\u00a0 \u00a0 Penn State College of Medicine\u00a0 \u00a0Postdoctoral Scholar – Statistical Genetics and Bioinformatics<\/em><\/p>

Nov. 2021- Oct. 2022\u00a0 \u00a0 SEMA4\u00a0 \u00a0 Sr.<\/em>\u00a0Bioinformatics Scientist<\/em><\/p>

Nov. 2022\u5e74- Dec. 2023\u00a0 \u00a0 META\u00a0 \u00a0Sr.Data Engineer, Analytics<\/em><\/p><\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Fang has a wide range of research interests, covering multiple fields including Bioinformatics, Genomics, Medical Genetics, and Molecular Biology. He possesses profound expertise in big data analysis and computational model building, especially adept at using artificial intelligence and machine learning methods to decipher complex genetic data. Additionally, Fang is dedicated to exploring how to apply genetic research findings to clinical practice, aiming to improve disease prevention and treatment outcomes. At the School of Medicine, Tongji University, and Shanghai East Hospital, Chen Lab will continue to collaborate closely with clinical teams, promoting the deep integration of genetic big data research and clinical practice, striving to make greater contributions to the health of the nation.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Members<\/strong><\/h2>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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