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DTSTAMP:20260711T135807Z
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DTSTART:20170919T230000Z
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DESCRIPTION:The immuno-oncology approach leverages on the unique capability
  of the immune system to recognize and kill tumour cells. This action is h
 ampered by escape mechanisms put in place by tumour cells like\, for insta
 nce\, the engagement immune checkpoints\, i.e. inhibitory molecules that m
 odulate the amplitude and duration of immune responses. Immunotherapies th
 at block checkpoint molecules are amongst the most promising approaches in
  immuno-oncology for the enhancement of antitumour immunity. Thanks to hig
 h-throughput technologies\, such as next-generation sequencing (NGS) and p
 roteomics\, we have now access to large-scale tumour data that can be used
  to investigate the interplay between tumour and immune cells and the role
  of the immune system in tumour progression and response to therapy. In th
 is course\, you will learn to use bioinformatics tools and mathematical mo
 delling techniques operating on high-throughput tumour data\, in order to 
 extract features that can be used to characterise this complex tumour-immu
 ne cell interface\, such as:\ntumour antigens recognized by T cells\ntumou
 r-infiltrating immune cells\nderegulated signalling pathways in cancer and
  immune cells\nA fully practical\, hands-on approach will ensure that the 
 newly acquire skills can be used with a great deal of autonomy.\nTarget Au
 dience:\nMotivated researchers\, clinicians\, and students who want to gai
 n an understanding on how bioinformatics tools and simple (logic-based) mo
 delling approaches can be used to investigate the tumour-immune cell inter
 face and its underlying signalling pathways from high-throughput data.\nCo
 urse Pre-Requisites:\nProgramming/scripting skills are helpful\, but not m
 andatory. An understanding of elementary operations with R will be require
 d. Elementary command line instructions in UNIX will be used\, so minimal 
 familiarity with navigation in directory trees\, copying files and folders
 \, etc. will be needed. \nInstructors:​\n           \nFrancesca F
 inotello received her PhD in Bioengineering in 2014 from the Department o
 f Information Engineering\, University of Padova (Italy). Her PhD thesis\,
  entitled "Computational methods for the analysis of gene expression from 
 RNA sequencing data"\, was awarded with the "Marco Ramoni" doctoral resear
 ch award by the Italian National Bioengineering Group. She has an extensiv
 e experience on computational methods for the analysis of different types 
 of next-generation sequencing (NGS) data\, including RNA-seq and 16S ribos
 omal RNA gene sequencing of the human microbiota. Currently\, she is a pos
 tdoctoral researcher in the Division of Bioinformatics of Medical Universi
 ty of Innsbruck (Austria). She is interested in bioinformatics and computa
 tional biology for cancer immunology and precision medicine\, with a parti
 cular focus on in silico prediction of tumor neoantigens and deconvolution
  of tumour-infiltrating immune cells from NGS data. She is principal inves
 tigator of the research project "QuanTIseq: dissecting the immune contextu
 re of human cancers" funded by the Österreichischen Krebshilfe Tirol (
 Austria) and aimed at developing a computational tool for the quantificati
 on of immune cell fractions from RNA-seq data of cell mixtures.\n      
      Affiliation: Division of Bioinformatics\, Medical University of I
 nnsbruck\, AT\n \nFederica Eduati received her PhD in Bioengineering in 
 2013 from the University of Padova\, with a thesis (awarded the "Paolo Dur
 st" best Italian PhD Thesis Award in Bioengineering) focusing on mechanist
 ic modelling aspects of both large- and small-scale biological systems. In
  2009 she participated to the DREAM4 "Predictive signaling network modelin
 g" challenge classifying as best performing team. In 2011-2012 she was a v
 isiting predoctoral fellow for 8 months in the Systems Biomedicine group a
 t EBI. Since February 2013 she is a Postdoctoral EIPOD fellow - Marie Curi
 e Fellow at EMBL (UK and Germany). Since May 2016 she is also a visiting s
 cientist at JRC-COMBINE in RWTH Aachen (Germany). Currently\, her main res
 earch interest is the investigation of why patients differentially respond
  to cancer therapy and how we can suggest personalized therapy. In particu
 lar\, she is interested in approaching this problem by investigating signa
 lling pathways\, their deregulation in cancer and the specific effect of t
 argeted therapy\, using dynamic mathematical modelling approaches and mach
 ine learning techniques. She has also been working on the development of a
  microfluidics platform\, which allows drug screening of live cells obtain
 ed from patient biopsies in a fast and cost-effective way. In 2013 she was
  also co-organizer of the NIEHS-NCATS-UNC DREAM Toxicogenetics Challenge\,
  where 213 registered participants from more than 30 countries had to pred
 ict cell line-specific cytotoxicity to chemical compounds based on genomic
  data and chemical attributes.\n           Affiliation: European Mo
 lecular Biology Laboratory (EMBL)\, Heidelberg\, DE\; JRC-COMBINE (RWTH Aa
 chen)\, Aachen\, DE\n \nProgram:\nYou can find here the detailed program.
 \n \nRegistration: \nRegister using here until August the 30th\n \nCon
 tact: For any questions about this course\, please contact Pedro Fernandes
  (e-mail address below)
LOCATION:Instituto Gulbenkian de Ciência
SUMMARY:IO17 - Large-scale bioinformatics for Immuno-Oncology
URL;VALUE=URI:http://gtpb.igc.gulbenkian.pt/bicourses/IO17/
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