Abstract: Shotgun metagenomics has uncovered a substantial amount of diversity in the human microbiome, but a large fraction of the sequences in a metagenome remains uncharacterized. In my talk I will show how new computational methods can (i) improve the resolution of metagenomic analysis to profile single microbial strains, (ii) uncover the still hidden diversity of the human microbiome, (iii) perform microbial transmission inference, and (iv) extend the analysis to tens of thousands of metagenomics. I will also discuss some biomedical applications for these analyses including oral, infectious, and non-communicable diseases.

Bio: Nicola Segata, Ph.D., is Professor and Principal Investigator in the CIBIO Department at the University of Trento (Italy) and Principal Investigator at the European Institute of Oncology in Milan (Italy). His lab (http://segatalab.cibio.unitn.it/) comprises more than 20 researchers and employs experimental metagenomic tools and novel computational approaches to study the diversity of the microbiome across conditions and populations and its role in human diseases. The projects in the lab bring together computer scientists, microbiologists, statisticians, and clinicians and are generally focused on profiling microbiomes with strain-level resolution and on the meta-analysis of very large sets of metagenomes with novel computational tools.