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FRANCESCA BUFFA

FRANCESCA BUFFA
Full Professor
Department of Computing Sciences

Courses a.y. 2023/2024

20880 MACHINE LEARNING LAB
30557 AI LAB
30592 TOPICS IN COMPUTATIONAL MODELLING: FROM INFORMATION THEORY TO EVOLUTIONARY MODELS

Courses previous a.y.

Teaching is a natural complement to research, and essential to form the next generation of computational and data scientists. I aim to help providing them with the necessary knowledge to tackle the big and complex data challenges we are currently facing in biology and medicine.


Biographical note

I am Full Professor at the Department of Computing SciencesBocconi University. I am the recipient of a European Research Council Award with sits at Bocconi University, where I supervise a team delivering novel computational tools, and the University of Oxford, where I supervise a lab generating and analyzing genomics and high-throughput screen data. Prior to this I was a Full Professor of Computational Biology and Cancer Genomics, and Group Leader, at the University of Oxford, United Kingdom. I hold a Ph.D. in Physics from the University of London, United Kingdom, and a degree in Theoretical Physics from the University of Turin, Italy.


Research interests

My main research topic is Artificial Intelligence in Life Sciences. I focus on the application of machine learning to biomedicine, genomics - the study of the structure, expression, function and evolution of the genome, and transcriptomics - the study of the complete set of RNA transcripts that are produced by the genome in a specific context and time.

As rapid developments in genomics, transcriptomics and other “omics” are revolutionizing biology and medicine, powerful computational methods are needed to translate this data into knowledge, and ultimately to improve human health.


Selected Publications

M. Di Giovannantonio ; BH. Harris; P. Zhang; I. Kitchen-Smith; L. Xiong; N. Sahgal; G. Stracquadanio; M. Wallace; S. Blagden; S. Lord; D. Harris; AHL. Harris; FM. Buffa
Heritable genetic variants in key cancer genes link cancer risk with anthropometric traits
Journal of Medical Genetics, 2020

A. Dhawan; A. Barberis; WC. Cheng; E. Domingo; C. West; T. Maughan; JG. Scott; AL. Harris; FM. Buffa
Guidelines for using sigQC for systematic evaluation of gene signatures
Nature Protocols 14(5):1377-1400, 2019

D. Voukantsis; K. Kahn; M. Hadley; R. Wilson; FM. Buffa
Modeling genotypes in their microenvironment to predict single- and multi-cellular behaviour
Gigascience., 2019

M. Pollak; K. Bradley; S. Wigfield; T. Metcalf; A. Thompson; FM. Buffa
Integrated Pharmacodynamic Analysis Identifies Two Metabolic Adaption Pathways to Metformin in Breast Cancer.
Cell Metabolism, 2018


S. Haider; A. McIntyre; RG. van Stiphout ; LM. Winchester; S. Wigfield; AL. Harris; FM Buffa
Genomic alterations underlie a pan-cancer metabolic shift associated with tumour hypoxia
Genome biology, 2016