Dr. Xing Li is an Assistant Professor and Associate Consultant in Division of Biomedical Statistics and Informatics, Department of Health Science Research at Mayo Clinic, the best hospital by U.S. News & World Report. Dr. Li completed his PhD in Bioinformatics from The University of Michigan at Ann Arbor, Michigan, USA. Dr. Li also hold a Master Degree in Biochemistry and Molecular Biology and Bachelor Degree in Microbiology. Dr. Li’s research interests focus on machine learning, bioinformatics, and statistical data mining in large scale data in biomedical research, such as next generation sequencing data (whole genome sequencing, RNA-seq, microarray data), in the file. He has published more than 20 peer-reviewed papers in reputed journals and book chapters in the fields of Bioinformatics and Biostatistics, cancer research, cardiovascular disease, embryonic stem cell (ESC) and induced pluripotent stem cell (iPSC) research, and human genomics, genetics and development, and Microbiology. Dr. Li’s publications have been highlighted as Journal Cover Stories, Journal Featured Articles, Highlights Section Papers, Must Read by Faculty 1000, and ESC & iPSC News, etc. Dr. Li has been developing data analysis tools, such as RCircle and PCA3d, etc. Dr. Li is also a member of American Association for Cancer Research (AACR), International Society for Computational Biology (ISCB), American Statistics Association (ASA) and American Heart Association (AHA).
Professor in Bioinformatics, Biology Department, Miami University, Ohio, USA
Research Assistant Professor of Biomedical Informatics, Vanderbilt University
I am an Assistant professor at Department of Biochemistry, State University of New York at Buffalo. I have expertise and extensive experience with developing and applying computational approaches for transcriptional and epigenetics regulation studies. As a postdoctoral fellow at Dana-Farber Cancer Institute, I developed widely used open-source algorithms, including MACS (cited over 3,200 times according to Google Scholar) to analyze ChIP-seq data, and an integrative platform for comprehensive analyses on cis-regulatory elements (http://cistrome.org/ap), which has over 3,000 users. I was a member of the Data Analysis Center and Analysis Working Group of the ENCODE and modENCODE consortium and was involved in deciphering functional elements through analyzing high-throughput profiles of chromatin factors and in comparing chromatin features between fly, worm and human genome. I have actively participated in the development of ChIP-seq guidelines for the broad scientific communities. My laboratory at University at Buffalo is focused on studying transcriptional and epigenetic regulatory mechanisms, and the influence of the genetic variations at regulatory elements.
Nick works as an Independent Research Fellow in the Institute for Microbiology and Infection at the University of Birmingham, sponsored by an MRC Fellowship in Biomedical Informatics. His research explores the use of cutting-edge genomics and metagenomics approaches to the diagnosis, treatment and surveillance of infectious disease. Nick has so far used high-throughput sequencing to investigate outbreaks of important pathogens such as Pseudomonas aeruginosa,Acinetobacter baumannii and Shiga-toxin producing Escherichia coli. His current work focuses on the application of novel sequencing technologies such as the Oxford Nanopore for genome diagnosis and epidemiology of important pathogens, including most recently real-time surveillance of the Ebola outbreak in West Africa. A more general aim is to develop bioinformatics tools to aid the interpretation of genome and metagenome-scale data in routine clinical practice in collaboration.
Tao Lu Professor, Department of Medicine, State University of New York.
Research interests include: Clinical research of infectious diseases; immunology; Diabetes; Signaling pathway; Endocrinology; Psychiatry; Respiratory Medicine; Sports medicine
Professor, Graduate School of Library & Information Science (GSLIS), National Center for Supercomputing Applications (NCSA), and Dept. of Computer Science at UIUC; Director, Center for Informatics Research in Science & Scholarship (CIRSS).
Previously Professor at the Dept. of Computer Science & Genome Center, UC Davis.
MS in Computer Science from U Karlsruhe (now KIT), PhD in Computer Science from U Freiburg (Germany). Research scientists at SDSC/UCSD until 2004.
My group is interested in investigating the processes of evolution and biology using computational methods. Our focus is on sequencing data, and are developing methods from early data analysis (read mapping, variant calling) to inference methods to investigate evolutionary questions in population genetics.
The Vsevolod Makeev Head of Department of Computational Systems Biology, Vavilov Institute of General Genetics, Russian Academy of Sciences; Professor at Moscow Institute (University) of Physics and Technology, Deputy Chair of Bioinformatics; Past Head of the Laboratory of Bioinformatics, State Research Centre of Genetics and Selection of Industrial Microorganisms.
Isabelle Mansuy is Professor in Neuroepigenetics at the Medical Faculty of the University of Zürich (UZH) & the Department of Health Science and Technology of the ETHZ.
She is a member of the Swiss Academy of Medical Science, the Research Council of the Swiss National Foundation, of EMBO, and elected Chevalier dans l'Ordre National du Mérite in France.
Associate Professor Bioinformatics, Department of Bioinformatics and Plant Biotechnology, Ghent University, Belgium; VIB department Plant Systems Biology. Associate Professor Bioinformatics, Department of Microbial and Molecular Plant Sciences, KU Leuven, Belgium. Recipient of the DSM award 2000. Recipient of the Biannual Siemens award 2002. Associate editor of BMC Release notes, BMC Bioinformatics, Journal of Integrative Omics
Radu Marculescu is a Professor in the Dept. of Electrical and Computer Engineering at Carnegie Mellon University, USA. He received his Ph.D. in Electrical Engineering from the University of Southern California in 1998.
Radu's current research focuses on developing methods and tools for modeling and optimization of embedded systems, cyber-physical systems, social networks, and biological systems. Radu Marculescu is a Fellow of IEEE cited for his contributions to the design and optimization of on-chip communication for embedded multicore systems.