Development and application of tools for microbiome studies
Microbiome research is a rapidly growing area of science. Over the last decade, the number of microbiome sequencing studies has expanded enormously, exploring the intricate communities of microbes within soil, water, the built environment, and the human body, amongst others. Within the human body, these studies can discover links between communities of microbes and many clinical outcomes, which elucidate the role of the human microbiome in complex disease development, progression, and treatment responses. Microbiome studies focusing on bacteria, archaea, viruses, and fungal communities have uncovered a wealth of novel species and functionalities. These findings suggest an exciting opportunity to develop new preventive and therapeutic strategies and to advance precision in disease diagnosis, risk stratification, and treatment decision-making. However, the unique features of microbiome data render many standard statistical and computational methods inadequate and hinder our ability to make robust conclusions about the role of the microbiome. Therefore, there is a need to ensure that adequate expertise and infrastructure is in place to meet the challenge of analyzing the data generated as well as a robust and reliable framework for interpreting the data.
This is a timely session to promote involvement of more bioinformatics and statistics researchers (junior and senior scientists) in the exciting field of microbiome science. With direct applications to ecology, evolution, microbiology, and human health, this session will be of broad interest. Many of the approaches employed in metagenomic research extend beyond a single system; methods for studying the human microbiome are the same approaches taken in the investigation of the natural and built environments. Invited and contributed talks will present: (1) different computational and statistical methods for analyzing microbiome data sets, and (2) investigations of microbiomes uncovering new insight into functions and dynamics.
Dr. Sailendharan Sudakaran, Microbiome Hub Manager, Wisconsin Institute for Discovery, University of Wisconsin Madison, Sudakaran@wisc.edu
Prof. Catherine Putonti, Associate Professor, Department of Biology, Computer Science, and Microbiology and Immunology, Director of Bioinformatics Program, Loyola University Chicago. firstname.lastname@example.org
Prof. Zhengzheng Tang, Assistant Professor, Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison
Prof. Karthik Anantharaman, Assistant Professor of Bacteriology, University of Wisconsin-Madison
Prof. Erik Wright, Assistant Professor, Department of Biomedical Informatics, University of Pittsburgh
Prof. Catherine Putonti, Associate Professor, Department of Biology, Computer Science, and Microbiology and Immunology, Director of Bioinformatics Program, Loyola University Chicago.
Prof. Michael Burns, Assistant Professor, Department of Biology, Loyola University Chicago.
Prof. Qunfeng Dong, Associate Professor, Department of Public Health Sciences and Director, Center of Biomedical Informatics, Loyola University Chicago
Prof. Michael Zilliox, Assistant Professor, Department of Public Health Sciences, Loyola University Chicago