MCBIOS 2017 Workshops


Workshop - I

MedDRA Workshop

Anna Zhao-Wong, MD, Ph.D., Deputy Director, MedDRA MSSO

MedDRA is the ICH standard medical terminology to facilitate sharing of regulatory information internationally for medical products used for use on humans. MedDRA is used in the registration, documentation and safety monitoring of medical products both before and after a product has been authorized for sale.
MedDRA workshop provides an understanding of the scope, hierarchical structure, and characteristics of MedDRA. Navigating MedDRA terminology using MedDRA Web-Based Browser is included.  While offering an overview of the features of MedDRA that relate to the analysis and retrieval of MedDRA-encoded data, the session describes the use of MedDRA to retrieve and present aggregated data, based on the principles outlined in the MedDRA Data Retrieval and Presentation: Points to Consider document. An introduction of Standardised MedDRA Queries (SMQs), an analytical feature of MedDRA, and their application in the investigation of drug safety issues are also provided.The workshop is designed for individuals whose work involves MedDRA or MedDRA-coded data, such as mining FAERS data, mapping terminologies involving MedDRA, etc.

Dr. Anna Zhao-Wong is the Deputy Director and the Manager of Terminology Development and Services of the Maintenance and Support Services Organization (MSSO). She has led MedDRA development projects, such as the expansion of medication error and medical device adverse event terms in MedDRA, and provides medical support of terminology maintenance. Additionally, as one of the MSSO trainers, Dr. Zhao-Wong has conducted face-to-face and webinar training courses for participants from regulatory authorities and the biopharmaceutical industry. Dr. Zhao-Wong received her M.D. from Beijing Medical University and Ph.D. from the Uniformed Services University of the Health Sciences. She joined the MSSO in the year 2000.


Workshop II

Next-Generation Sequencing (NGS) datasets analysis using Galaxy platform

Binsheng Gong, Ph.D.,Visiting Scientist, Division of Bioinformatics and Biostatistics, NCTR/FDA

This workshop is for users who want to acquire the skills required to analyze the Next-Generation Sequencing (NGS) datasets using Galaxy platform. The event is open to all the students, postdocs as well as faculty members who are interested in NGS data processing and analysis with general workflows. The workshop will be focus on the basic usage of Galaxy platform, with demos covering NGS data quality assessment, read alignment to the genome, gene expression quantification and differential gene expression analysis. Galaxy is an open source, web-based platform for data intensive biomedical research. It provides hundreds of tools for next-generation sequencing (NGS) data analysis, including but not limited to genetic variance calling, transcriptomic profiling, DNA methylation, microbial genomics, pan-genomics, metagenomics, etc. With Galaxy, Wet-lab researchers can manage their data and do most general analysis with short-term training. Galaxy also provides a good way to make research more transparent and more accessible, and improve the reproducibility and robustness scientific research.

Dr. Gong is a Visiting Scientist in Division of Bioinformatics and Biostatistics at FDA’s National Center for Toxicological Research (NCTR/FDA), with expertise in next-generation sequencing technologies and high-throughput data analysis. His studies have significantly advanced the application of bioinformatics methods and systems biology strategies in basic biological study and translational medicine and his research achievements have been recognized with several awards from U.S. FDA and from China. He has served as reviewer for multiple prestigious journals such as Oncotarget, PLoS ONE, Scientific Reports, etc. Dr. Gong has been involved as one of the major investigators in the FDA led SEquencing Quality Control (SEQC) project, and he is the leading author of one Nature Biotechnology paper and co-authors of several others produced by SEQC project. Dr. Gong has more than 30 research papers published in prestigious journals such as Nature Biotechnology, Genome Biology, Nucleic Acid Research, etc. His researches have received more than 350 citations from government agencies, armies, pharmaceutical and food companies and research institutes. Dr. Gong was one of the chapter editors of the first bioinformatics text book for higher institutions in China.


Workshop III

PubChem

Yanli Wang, Ph.D., Lead Scientist, National Center for Biotechnology Information (NCBI), Washington D.C.

PubChem is a database of chemical molecules and their activities against biological assays. The system is maintained by the National Center for Biotechnology Information (NCBI), a component of the National Library of Medicine, which is part of the United States National Institutes of Health (NIH). PubChem can be accessed for free through a web user interface. Millions of compound structures and descriptive datasets can be freely downloaded via FTP. This workshop will provide hands-on experience on using PubChem database.

Dr. Yanli Wang obtained her PhD in computational biology in 1995 from Peking University, China. She completed postdoctoral studies from the National Institute of Cancer (NCI) and National Center for Biotechnology Information (NCBI) of the National Library of Medicine (NLM) during 1995-1998, and since then she has continued to work at NCBI on various research and informatics projects. She is currently a lead scientist at NCBI and primarily responsible for managing the PubChem BioAssay resource. Dr. Wang also mentors several postdoctoral fellows and has published over 40 papers in international journals.

1. Pubchem database access

2. PubChem Hands-on Practice


Workshop IV

Next-generation sequencing (NGS) and Bioinformatics

Wenming Xiao, Ph.D. Research Principal Investigator, Division of Bioinformatics and Biostatistics, FDA NCTR, Jefferson, AR
 
Recent technology developments in next-generation sequencing (NGS) have opened completely new possibilities for the deep characterization of molecular mechanisms at various levels of cellular regulation providing information on substance-induced genomic variations, and on transcriptomic and epigenomic changes. These developments will strengthen our understanding of mechanisms-of-action and ultimately lead to a systems-wide analysis thus enabling the development of safer drugs, industrial chemicals, consumer products and improved regulation. This workshop will provide the overview of bioinformatics in NGS application for an enhanced understanding of underlying mechanisms of toxicity and potential utility in regulatory setting.
 
Dr. Xiao received his bachelor in biology from Xiamen University in 1989 and master in genetics from the Institute of Microbiology, Chinese Academy of Science in 1992. Later on, he moved to United States and finished Ph. D program in molecular genetics form the Medical College of Wisconsin in 1997 and master program in computer science from Marquette University in 1998. From 1998 to 2005, Dr. Xiao was bioinformatics scientist in GeneLogic, MetriGenix, and Celera Genomics. Since 2005, he joined the National Institute of Health as a contractor and then as a staff scientist at Center for Cancer Research, National Institute of Cancer. In Dec, 2014, Dr. Xiao joined Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, Food and Drug Administration. Dr. Xiao has numerous publications in peer-reviewed journals such as Nature, PNAS, N. Engl. J. Med, and Cancer Cell. In 2010, he received the NIH director award and NIH merit award for his contribution in Lymphoma Leukemia Molecular Profiling Program. During his early career in industry, Dr. Xiao defined and developed IT infrastructure and software/database solutions for genomics and microarray data. His recent focus is to develop informatics tools in supporting next generation sequencing technology for intramural research at the NIH for various applications such as, genome assembly, ChIP-Seq, RNA-Seq, Exome-Seq and digital gene expression.