Date: 14 November 2017 @ 09:00 - 00:00

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The implementation of cancer genomics into the clinic is becoming a reality. Personalized medicine or Precision medicine as other authors refers, uses molecular data of a specific patient to guide clinical decisions such as prevention, diagnosis and treatment. This will revolutionize healthcare and will play a dominant role in the future of cancer therapy. Bioinformatics analyses are essential to identify patients who will benefit from treatment based on their molecular profile, and to tailor chemotherapeutic regimens accordingly.

The aim of the course is to present a complete computational pipeline for the analysis and interpretation of Next-Generation Sequencing (NGS) data such as exome sequencing or targeted panels that are commonly used in the clinic.

We will address the implementation of large-scale genomic sequencing in clinical practice and the recently developed computational strategies for the analysis of NGS data with a particular emphasis on the interpretation of the results, selection of biomarkers of drug response and afford opportunities to match therapies with the characteristics of the individual patient's tumour. 

Exercises and case studies focused on cancer will be used to illustrate the principles of how genetics influence led to refining diagnoses and personalized treatment of cancer disease.
Target Audience:
This course is intended for working healthcare professionals and Bioinformaticians working in the area.
Course Pre-Requisites:
The course assumes that attendees are not intimidated by the prospect of gaining experience working on UNIX-like operating systems (including the shell, and shell scripting). Attendees should understand some of the science behind high-throughput DNA sequencing and sequence analysis, as we will not go deeply into underlying theory (or the mechanics of given algorithms, for example) as such. What will be taught are technical solutions for automating and sharing such analyses in reusable compute environments, which will include (but is not limited to) beginner-level programming, and basic Linux provisioning. General computer literacy, (e.g. editing plain text data files, navigating using the command line) will be assumed. (
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) Note: An optional free session will be arranged with the participants that may be interested, on the EVE of the first day (Monday, Nov 13th at 4PM), where we will ensure that every participant willing to attend can use the Linux operating system at the required level.
Instructors:​
           
Fátima Al-Shahrour obtained her PhD from Universidad Autónoma de Madrid (UAM) in 2006. During her PhD she worked at the Bioinformatics Unit at Spanish National Cancer Research Center (CNIO, Madrid, Spain) and Centro de Investigaciones Príncipe Valencia (Valencia, Spain). During this period, her research work dealt with the development of new Bioinformatics tools for microarray gene expression analysis, with a particular focus on computational methods for the functional interpretation of high-throughput experiments. In 2007, she joined the Computational Biology and Bioinformatics group at Cancer Program at Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard (Cambridge, USA). In 2008, she got a staff position at Broad Institute of MIT and Harvard as a Computational Biologist. During this period, her research was focused on the study the biology and treatment of cancer under a genomic perspective using hematopoiesis as a model system. In 2012 she joined the Spanish National Cancer Research Centre (CNIO) to lead the Translational Bioinformatics Unit (TBU) in the Clinical Research Programme and since 2017 she is leading the Bioinformatics Unit (BU).
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The CNIO Bioinformatics Unit (BU) belongs to the Structural and Biocomputing Programme. This is a group with a large trajectory in bioinformatics for functional genomics, field in which the group has published numerous papers as well as developed distinct applications and programs widely used by the scientific community. BU's major research activity is focused on the development of new computational methodologies to perform genomic analysis of cancer patients' data, in order to identify new biomarkers and mechanisms of drug response. The main goal is to translate this knowledge into effective treatments for cancer patients. Since 2013, we extensively collaborate with hospitals to analyze next-generation sequencing data from patient's tumors. During this period, we have applied our analytical pipeline for the categorization and interpretation of patient's tumors and match them to effective drugs or treatments based on their genomic alterations.
           Affiliation: Centro Nacional de Investigaciones Oncológicas, Madrid, ES
Javier Perales is a PhD student working under the supervision of Fátima Al-Shahrour & Alfonso Valencia, at the Spanish National Cancer Research Centre. During his education, he has acquired knowledge in Molecular Biology, Genetics and Computational Biology. His research activity is focused on the genomic characterization of patient tumours by Next-Generation Sequencing technologies. He is interested on the development and integration of computational approaches for cancer genomics data in order to improve our understanding about the individual patient's disease.
           Affiliation: Centro Nacional de Investigaciones Oncológicas, Madrid, ES
Elena Piñeiro is a Bioinformatician working in the Bioinformatics Unit of the CNIO. Her work is mainly focused on the elaboration of pipelines for the analysis and prioritization of genomic variations obtained through NGS technologies and on the construction of a methodology for the personalized drug assignation according to the particular genomic profile of each patient.
           Affiliation: Centro Nacional de Investigaciones Oncológicas, Madrid, ES
 
Program:
You can find here the detailed program.
 
Registration: 
Register using here until October the 18th
 
Contact: For any questions about this course, please contact Pedro Fernandes (e-mail address below)

Venue: Instituto Gulbenkian de Ciência

Country: Portugal

Postcode: 2781-901


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