教师基本信息：
姓名：石乐明 Leming Shi
职称：教授 Professor
电子邮箱：lemingshi@fudan.edu.cn
办公地点：D610
办公电话：021-31246746
个人网页/课题组主页：https://chinese-quartet.org/
研究方向：
Dr. Shi’s research aims to improve the success rate of drug development and the clinical efficacy rate of therapeutics with high-quality biomedical big data. Dr. Shi’s research interests include chemogenomics, pharmacogenomics, precision medicine, biomedical big data, bioinformatics, and chemoinformatics. By ensuring the reproducibility and reliability of multi-omics data generation, analysis, integration, and interpretation, we aim to discover biomarkers and drug targets for disease prevention, diagnosis, and treatment.
石乐明，男，1964年出生于湖南益阳。2011年加入复旦大学，现任生命科学学院和附属肿瘤医院特聘教授。国家特聘专家、国家重点研发计划重点专项项目负责人(2019和2023)、获10项美国和国际发明专利授权、中国专利金奖(2017，第4完成人)、上海市科技进步奖一等奖(2020，第7完成人)；深圳微芯生物共同创始人，抗癌新药西达本胺和抗糖尿病新药西格列他钠共同发明人；获批全基因组和全转录组国家一级标准物质10项；发表SCI论文200余篇(含20篇Nature Biotechnology)，SCI他引20,000多次，h-index 70，编著有《大数据与精准医学》一书(2018)；共同创立国际MAQC组学大数据质量控制学会，担任其首任主席(2017-2018)、首席科学官和董事；主导或参与制定多项国际ISO、CLSI及IUPAC组学标准及FDA指南。其工作被同行认为“从根本上改变了组学数据分析的实践，促使基因组医学成为现实”。
毕业于湖南大学(1985，学士，分析化学)、中国科学技术大学(1988，硕士，计算化学)和中国科学院过程工程研究所(1991，博士，计算化学)，后留所任助理研究员(1991)和副研究员(1993)；曾于美国凯斯西储大学和美国国家健康研究院肿瘤研究所(NIH/NCI)从事博士后研究(1994-1997)，并任职于美国食品药品监督管理局(FDA)、Wyeth和BASF (1997-2001)。
2001年参与创办深圳微芯生物，创建基于化学基因组学的药物研发平台，开发的多个创新化合物在中国、日本和美国进入临床试验，其中1.1类原创新药HDAC (1/2/3/10) 亚型选择性抑制剂西达本胺被中国NMPA批准上市，用于治疗外周T细胞淋巴瘤(2014)和乳腺癌(2019)，西达本胺治疗成人T细胞白血病(ATL)的上市申请获日本PMDA批准(2021年)；新型胰岛素增敏剂PPAR (α/γ/δ)全激动剂西格列他钠被中国NMPA批准上市 (2021)，用于治疗2型糖尿病；微芯生物于2019年在上海科创板上市(688321.SH)。
2003年重新加入美国FDA，发起成立关于基因芯片和新一代测序的国际组学大数据质量控制联盟MAQC/SEQC，先后就基因表达谱数据、生物标志物和预测模型、转录组测序数据以及基因组DNA测序数据的质量控制和标准化分析进行了系统的探索。其研究成果由Nature Biotechnology杂志分别于2006年、2010年、2014年和2021年以4个专辑发表，促进了美国FDA基因组学指南和有关国际标准的制定。其工作直接促成了国际MAQC组学大数据质量控制学会(www.maqcsociety.org)的成立，旨在提高多组学高通量技术的可靠性和可重复性，为精准医学保驾护航(Shi L et al., Nature Biotechnology 2017)。
Dr. Leming Shi is a professor at the School of Life Sciences and Shanghai Cancer Center of Fudan University since 2011. He is a National Distinguished Expert (2010), Principal Investigator of the National Key R&D Project of China (2019 and 2023), and the recipient of ten issued US and PCT patents and the WIPO-SIPO Award for Chinese Outstanding Patented Invention (2017). Dr. Shi is a co-founder of Chipscreen Biosciences and a co-inventor of the marketed anticancer drug Chidamide (2014) and antidiabetic drug Chiglitazar (2021). He has published over 200 peer-reviewed papers (20 in Nature Biotechnology) with >20,000 citations by SCI journals and an h-index of 70, and is the chief editor of the book “Big Data and Precision Medicine” (2018). As a co-founder of the International MAQC Society, Dr. Shi served as its founding president (2017-2018), and is its Chief Science Officer and a member of board of directors. Dr. Shi (co-)led the development of several ISO and CLSI standards and FDA guidance on genomics.
Dr. Shi received his PhD in computational chemistry from the Chinese Academy of Sciences in Beijing (1991); MSc in computational chemistry and chemometrics from the University of Science and Technology of China in Hefei (1988); and BSc in analytical chemistry from Hunan University in Changsha (1985). He conducted postdoctoral training at Case Western Reserve University (with Dr. Gilles Klopman, 1994-1995) and the NIH/NCI (with Dr. John Weinstein, 1995-1997), and was a research scientist at US FDA, Wyeth (now Pfizer), and BASF before co-founding Chipscreen Biosciences in 2001.
As a co-founder of Chipscreen, Dr. Shi co-developed a chemogenomics-based drug discovery platform, leading to the discovery of several novel small-molecule drug candidates with promising efficacy and safety profiles in anticancer and antidiabetic clinical trials in China, Japan, and the US. One novel subtype-selective HDAC inhibitor (Chidamide) was approved for treating T-cell lymphoma (2014) and advanced breast cancers (2019) in China, and for treating adult T-cell leukemia in Japan (2021). One PPARα/γ/δ pan-agonist (Chiglitazar) was approved for treating type 2 diabetes (2021) in China. Chipscreen went to IPO in August 2019 at Shanghai Stock Exchange (688321.SH).
As a principal investigator at the US FDA, Dr. Shi conceived and led the MicroArray and Sequencing Quality Control (MAQC/SEQC) consortia for quality control and standardization on the generation, analysis, and interpretation of transcriptomic and genomic data, publishing four special issues in Nature Biotechnology. These efforts, fundamentally changed the practice of genomic data analysis and helped make genomic medicine a reality, leading to the launch of the International Massive Analysis and Quality Control (MAQC) Society (www.maqcsociety.org) to enhance the reproducibility of high-throughput technologies for precision medicine (Shi L et al., Nature Biotechnology 2017).
授课情况：
《大数据与精准医学》
“Big Data and Precision Medicine”
招生专业：
生物学、生物与医药、生物信息学、医学遗传学
Biology, biomedicine, bioinformatics, and medical genetics
科研项目：
1、 人体表型解析技术体系及标准体系研发，国家重点研发计划前沿生物技术重点专项，2023YFC3402500, 1697万元，2023年12月至2028年11月，项目负责人
2、 人类表型组学数据的质量控制与标准化研究，国家重点研发计划战略性国际科技创新合作重点专项，2018YFE0201600，1144万元，2019年8月至2022年7月，项目负责人
3、 组学大数据的质量控制与临床应用标准化研究，国家高技术研究发展计划(863计划)，2015AA020104，1609万元，2015年1月至2017年12月，项目负责人
4、 肿瘤高置信基因组突变分析方法学研究和优化，国家自然科学基金重点国际合作研究项目，31720103909，243万元，2018年1月至2022年12月，项目负责人
5、 高置信全基因组胚系变异标准数据集的构建和应用，国家自然科学基金面上项目，32170657，58万元，2022年1月至2025年12月，项目负责人
6、 多组学数据整合的质量控制方法和应用，国家自然科学基金面上项目，32370701，50万元，2024年1月至2027年12月，项目负责人
获奖情况：
1、邵志敏、江一舟、李大强、吴炅、余科达、黄薇、石乐明、胡欣、柳光宇、王中华、狄根红、李俊杰、马丁、肖毅、沈镇宙，中国乳腺癌分子分型和精准治疗的研究和成果推广，上海市科技进步奖一等奖，2020年。
2、鲁先平、李志斌、谢爱华、石乐明、李伯玉、宁志强、山松、邓拓、胡伟明，具有分化和抗增殖活性的苯甲酰胺类组蛋白去乙酰化酶抑制剂及其药用制剂(ZL03139760.3)，中国专利金奖，国家知识产权局和世界知识产权组织，2017年。
1. Zheng Y#*, Liu Y#, Yang J#, Dong L#, Zhang R#, Tian S#, …, Ding C*, Li J*, Fang X*, Shi L*. Multi-omics data integration using ratio-based quantitative profiling with Quartet reference materials. Nature Biotechnology, 42(7), 1133-1149 (2024).
2. Yu Y#, Hou W#, Liu Y#, Wang H#, Dong L#, …, Xu J*, Qian F*, Zhang R*, Shi L*, Zheng Y*. Quartet RNA reference materials improve the quality of transcriptomic data through ratio-based profiling. Nature Biotechnology, 42(7), 1118-1132 (2024).
3. Xiao W#*, Ren L#, …, Wang C*, Shi L*. Towards best practice in cancer mutation detection with whole-genome and whole-exome sequencing. Nature Biotechnology, 39(9), 1141-1150 (2021).
4. Fang LT#, Zhu B#, Zhao Y#, …, Hong H*, Shi L*, Wang C*, Xiao W*. Establishing community reference samples, data and call sets for benchmarking cancer mutation detection using whole-genome sequencing. Nature Biotechnology, 39(9), 1151-1160 (2021).
5. Jiang YZ#, Ma D#, Suo C#, Shi J#, Xue M#, Hu X#, …, Wang P*, Shi L*, Huang W*, Shao ZM*. Genomic and transcriptomic landscape of triple-negative breast cancers: subtypes and treatment strategies. Cancer Cell, 35(3), 428-440 (2019).
6. Shi L, …, Tong W. The international MAQC Society launches to enhance reproducibility of high-throughput technologies. Nature Biotechnology, 35(12), 1127-1128 (2017).
7. Su Z#, Łabaj PP#, Li S#, …, Kreil DP*, Mason CE*, Shi L*. A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequence Quality Control consortium. Nature Biotechnology, 32(9), 903-914 (2014).
8. Shi L#*, …, Wolfinger RD. The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models. Nature Biotechnology, 28(8), 827-838 (2010).
9. Guo L#*, …, Shi L*. Rat toxicogenomic study reveals analytical consistency across microarray platforms. Nature Biotechnology, 24(9), 1162-1169 (2006).
10.Shi L#*, …, Slikker W, Jr. The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements. Nature Biotechnology, 24(9), 1151-1161 (2006).