"Science is but a perversion of itself unless it has as its ultimate goal the betterment of humanity."
"Maybe the journey isn't so much about becoming anything.
Maybe it's about unbecoming everything that isn't you so you can be who you were meant to be in the first place."
"I saw the angel in the marble and carved until I set him free."
I am a Postdoc at the Robinson lab at the Institute of Molecular Life Sciences at the University of Zurich where I am working on the development of cutting-edge statistical methods in bioinformatics, mainly for high-throughput single-cell data.
Previously, I was a PhD student at the Department of Statistics at the University of Warwick, where I focused on stochastic Bayesian hierarchical models to investigate transcription in single cells.
In general terms, my interests are broad and lie in the development and application of statistical methods in computational biology.
2013 - 2017: PhD in Statistics. The University of Warwick (UK), Department of Statistics.
Thesis: "Bayesian Hierarchical Stochastic Inference on Multiple, Single Cell, Latent States from both Longitudinal and Stationary Data".
Supervisor: Prof Barbel Finkenstadt.
2010 - 2012: Master's degree in Statistics (110/110 cum laude). The University of Padua (Italy), Department of Statistical Sciences.
Dissertation: "A composite likelihood approach to predict the babies sex".
Supervisor: Prof. Bruno Scarpa. Co-supervisor: Prof. Nicola Sartori.
2007 - 2010: Bachelor degree in Statistics (110/110 cum laude). Sapienza University of Rome (Italy), Department of Statistical Sciences.
Dissertation: "A logistic analysis to predict the axillary lymph node status, in patients affected by breast cancer and with positive sentinel lymph node".
Supervisor: Prof. Maria Grazia Pittau.
Simone Tiberi, Helena L Crowell, Lukas M Weber, Pantelis Samartsidis and Mark D Robinson.
distinct: a novel approach to differential distribution analyses.
A pre-print is available on bioRxiv at: https://doi.org/10.1101/2020.11.24.394213.
Christian Sailer, Simone Tiberi, Bernhard Schmid, Juerg Stoecklin and Ueli Grossniklaus.
Apomixis and genetic background affect distinct traits in Hieracium pilosella L. grown under competition.
A pre-print is available on biorXiv at: https://doi.org/10.1101/2020.12.30.424832.
Massimo Cavallaro, Mark Walsh, Matt Jones, James Teahan, Simone Tiberi, Bärbel Finkenstädt and Daniel Hebenstreit.
Genome Biology (2021).
A pre-print is available on biorXiv at: https://doi.org/10.1101/514174.
Simone Tiberi and Mark D Robinson.
Genome Biology (2020).
Koen Van Den Berge*, Katharina Hembach*, Charlotte Soneson*, Simone Tiberi*, Lieven Clement, Michael I Love, Rob Patro, Mark Robinson.
Annual Review of Biomedical Data Science (2019). *joint first authorship.
Anthony Lee, Simone Tiberi and Giacomo Zanella.
Simone Tiberi, Mark Walsh, Massimo Cavallaro, Daniel Hebenstreit and Bärbel Finkenstädt.
Simone Tiberi, Bruno Scarpa and Nicola Sartori.
Statistical Methods in Medical Research (2018).
Augusto Lombardi, Stefano Maggi, Marzia Lo Russo, Francesco Scopinaro, Domenica Di Stefano, Maria Grazia Pittau, Simone Tiberi and Claudio Amanti.
Bioconductor R packages
BANDITS: Bayesian ANalysis of DIfferenTial Splicing
BANDITS is a Bayesian hierarchical model for detecting differential splicing, of both genes and transcripts, while accounting for sample-to-sample variability and mapping uncertainty.
distinct: a method for differential analyses via hierarchical permutation tests
distinct is a statistical method to perform differential testing between two or more groups of distributions. Unlike most methods for differential expression, distinct identifies both, differential patterns involving changes in the mean, as well as more subtle variations that do not involve the mean (e.g., unimodal vs. bi-modal distributions with the same mean).
Bioconductor Conference 2021, virtual, 4-6 August 2021.
European Young Statisticians Meetings 2021, virtual, 6-10 September 2021.
Conferences and workshops
European Bioconductor Meeting 2020, virtual, 14-18 December 2020. Slides available at: https://f1000research.com/slides/9-1450.
ISMB/ECCB 2019, Basel, 21-25 July 2019. Slides available at: https://f1000research.com/slides/8-1223.
IBS Channel Network Conference 2019, Rothamsted Research, 10-12 July 2019.
BITS Bioinformatics Italian Society Meeting 2019, Palermo, 26-28 June 2019.
ECCB EUROPEAN CONFERENCE ON COMPUTATIONAL BIOLOGY 2018. Athens, 8-12 September 2018.
IBC International Biometric Conference 2018. Barcelona, 8-13 July 2018.
BC2 Basel Computational Biology Conference 2017. Basel, 12-15 September 2017.
IBS Channel Network Conference 2017. Hasselt University, 24-26 April 2017.
Seminars and meetings
IMLS Research Progress Report, University of Zurich, 20 April 2018.
BIO612 - Seminars in Bioinformatics, University of Zurich, 18 April 2018.
Young research meeting (YRM), The University of Warwick,
8 March 2016
28 March 2014
19 November 2013
23 September 2013
Postgraduate Open Day, The University of Warwick,
25 November 2015
26 November 2014
Whole transcriptome sequencing data analysis. University of Pretoria (South Africa), February 1-8 2019.
Material available at: https://github.com/markrobinsonuzh/pretoria_rnaseq_course_feb2019.
Bioinformatics for Adaptation Genomics 2018, Weggis (Switzerland), 11-17 Feb 2018.
Theory and methods of RNA-seq studies: material available at: https://github.com/SimoneTiberi/BG4-2018.
University of Zurich:
Academic year 2016/2017, Fall Semester: STA121 - Statistical Modelling.
University of Warwick (tutorials):
Academic year 2015/2016, Term 1: ST301/ST413 - Bayesian Statistics & Decision Theory
Academic year 2015/2016, Term 1: ST333/ST406 - Applied Stochastic Processes
Academic year 2014/2015, Term 2: ST219 - Mathematical Statistics Part B
Academic year 2014/2015, Term 1: ST218 - Mathematical Statistics Part A
Academic year 2013/2014, Term 2: ST115 - Introduction to Probability
Academic year 2013/2014, Term 1: ST116 - Mathematical Techniques