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Key lab seminar by Dr. Tieliu Shi from East China Normal University,Jan. 11,(Thursday)
Authors:mujing    Time:2018-01-05    Read:64

Speaker: Tieliu Shi , PhD
                Professor of Bioinformatics & Computational Biology  
                 School of Life Sciences
                 East China Normal University
               Email: tieliushi01@gmail.com

 Time : 10:00-11:30 am , Jan. 11(Thursday)
 Venue: Room 300, SIBS Main Building, Yueyang Road 320
 Host:  Prof. Sijia Wang
                CAS-MPG Partner Institute for Computational Biology

Title:Standardized Disease Annotation Knowledge Bases for Precision Medicine



Precision medicine for disease prevention and treatment strategiest is currently the most popular practice in clinical application. However, these promising applications greatly rely on data mining, sharing and exchange. Currently, one of the major challenges for the application of big data is the lack of uniformly structured data in clinical practice, because different Healthy Information Systems and different Electronic Medical Records are applied by different hospitals, and different vocabularies are used to describe clinical observations and treatment strategies by different healthcare providers. The high disparity in clinical data among hospitals and healthcare providers is a significant obstacle for the data sharing and downstream analysis. To facilitate precision medicine in clinical applications, it is necessary to build a platform to standardize clinical information and use it for the integration of various clinical resources for individual patient’ precise diagnosis, prognosis, and therapeutic strategies.
To this end, we built systems to standardize and classify pediatric and rare diseases - PedAM (Pediatrics Annotation & Medicine) and eRAM (Encyclopedia of Rare Disease Annotation for Precision Medicine). Both platforms integrate biomedical resources and clinical data from Electronic Medical Records (EMRs) and to support the development of computational tools which will enable robust data analysis and integration. Currently, near 10 million abstracts from PubMed and 1 million full text articles from PubMed Central have been text-mined, the extracted sentences describing the disease-manifestation (D-M) and disease-phenotype (D-P) are all stored in our database and can be traced back to the original published papers through PubMed ID.
Currently, eRAM contains 15,942 diseases, with 27,329 unified human phenotype terms, 12,207 phenotypes from matched corresponding mouse phenotype ontology, 75,335 manifestations, when PedAM contains standardized 8528 pediatric disease terms (4542 unique disease concepts and 3986 synonyms).


石铁流 教授,博导。于1992年在中科院上海植物生理研究所(现中科院上海植物生理生态研究所)获得植物生理专业硕士学位。1999于美国Louisville大学获计算机硕士学位,2000年于Louisville大学获得分子生物学博士学位。2002年6月回国,加入到中科院上海生命科学研究院生物信息中心,担任副主任。2008年底加入到华东师范大学生命医学研究所,为生命科学学院特聘教授。 多年来从事生物信息学和计算系统生物学的研究。主要的研究方向是: 1. 临床信息标准化以及基因型表型的关联研究;2. 高通量数据(测序数据和蛋白质组学数据)分析及方法学开发;3. 整合临床信息和多组学数据的疾病基因及机理研究,生物分子标记的发现;4. 基因调控网络的研究和蛋白质相互作用网络的研究;5. 药物靶点,作用机理及药物副作用的研究,包括传统的中药。 主持和参与了多项国家863项目、973项目和“中国人类蛋白质组”等重大研究计划项目,国家自然科学基金项目。已在Nature Biotechnology,Nature Communication, Cell Research,Genome Biology 等杂志上发表100多篇SCI的研究论文,建立了一站式蛋白质组学数据分析平台、测序数据分析及疾病基因组的分析平台。已申请了各种疾病检测的专利十多项。 目前担任中国遗传协会生物大数据分会理事,上海植物生理学会理事和上海生物信息学学会理事,上海市基因健康专委会委员和上海市计算机生物信息学专委会委员。同时担任《中国科学–生命科学》(Science China-Life Sciences)杂志的常务编委,Pediatric Investigation杂志副主编等。



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