*Title: Reconstructing Cancer Progression Models *Abstract: Cancer is a disease characterized by the accumulation of alterations to the genome, which selectively make cancer cells fitter to survive, proliferate and move. The understanding of progression and evolution models that underlie this processes, i.e., the characterization of sequences of alterations that lead to the emergence of the disease, is a topic attracting much attention. Of course, the problem of reconstructing such models is not new; in fact, several methods for inferring progression models (and phylogenies) from cross-sectional samples have been developed since the late 90s. Recently, we have proposed a number of algorithms to reconstruct cancer clonal evolutionary models from a variety of cross-sectional data types, either "ensemble", "bulk" or "single cell". We perform our reconstructions using a variety of algorithms based on a “probability raising” score that guarantees statistical dependencies on the inferred precedence relations. Our methods are complementary to traditional phylogeny reconstructions ones. Within this context, we have proven the correctness of our algorithms and characterized their performance. Our algorithms are collected in a R BioConductor package “TRanslational ONCOlogy” (TRONCO) that we have successfully used as part of our "Pipeline for Cancer Inference" (PiCnIc) to analyse Colorectal Cancer (CRC) data from TCGA. The newest addendum to TRONCO is the “Temporal oRder of Individual Tumors” (TRaIT) a new collection of algorithms that can be used for single-cell (and multi-region) progression analisys of cancers. Web Sites: \* http://bimib.disco.unimib.it/ \* http://troncopackage.org *Speakers: Marco Antoniotti is an Associate Professor of Computer Science in the Department of Informatics, Systems and Communication of the Università Milano-Bicocca, Milan, Italy. Before that he was Senior Research Scientist of the NYU Courant Bioinformatics Group in New York and a Research Scientist at PARADES EEIG in Rome, Italy. From 1996 to 1997 post Doctoral fellow at University of California at Berkeley PATH Institute. He received his Ph.D in Computer Science from Courant Institute of Mathematical Sciences of New York University. His main research topics are Bioinformatics and Computational (Systems) Biology, Simulation, Verification and Language Design Issues. More recently he has - almost - become a Cancer Researcher, and, with his group, he is studying Cancer Progressions, Cancer Evolution and Personalized Therapies; all by analyzing different data types and data sources, including Single-cells. Marco Antoniotti is the author of several journal and conference papers and of several software projects; he has received support for his research from NSF, the Regione Lombardia (Italy), the Elixir european network, the European Commission under the H2020 program and the MCSA and COST actions and CRUK/AIRC/FA-AECC under the Accelerator Award scheme. *Date: Monday, 18th of November 2019, 12:00-13:00 *Location: Manno, Galleria 1, 2nd floor, room G1-201 *Doodle registration: Pizza (or alternative food) and drinks will be offered at the end of the talk. If you plan to attend the lunch, please register in a timely fashion (meaning at the latest at 9AM of the same day of the talk) at the following link so that we will have no shortage of food. https://doodle.com/poll/g3bbf2pthrxq7nxp If by any chance, after registering for a Pizza at the link above, you know you will not be able to attend the lunch, please cancel your registration asap.