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Back to 2020_02_18_noticia_TECNUN-tesis-JP-Romero

"I see my thesis as a contribution to the academic community that financial aid to better understand the various diseases."

Former student Juan Pablo Romero develops an algorithm that improves the accuracy of treatment for diseases such as cancer.

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PHOTO: Communication Service
18/02/20 12:06 Communication Service

Juan Pablo Romero, a native of Mexico, has won this year's award Extraordinary Doctoral Award offered by Tecnunfor developing an algorithm that improves the precision of treatment for diseases such as cancer. He proudly tells that "it is available in Bioconductor, one of the most important data instructions of bioinformatics algorithms, and that since it was uploaded to this database, it has been downloaded more than 4 thousand times." Juan Pablo Romero successfully completed the thesis two years ago, as he acknowledges, thanks also to the support of his directors Dr. Ángel Rubio and Dr. Francis Planes. Since then, he has been doing research at the department de Oncohematology de CIMA

1. What was the goal of your thesis?

The global goal of project consisted in the development of an algorithm (EventPointer) to be able to find alternative splicing events and analyze them statistically. altered due to the disease.

There are several scientific articles that talk about the cause-effect relationship of some genomic alterations in the development of various pathologies. One of these articles talks about the "Hallmarks of Cancer" and its authors define six characteristics common to all types of cancer that are used to explain the transformation of a normal cell into a malignant or tumor cell. Later on, evidence of the relationship of some alterations with these Hallmarks appeared and another one appeared article that makes a direct relationship of alternative splicing with the Hallmarks. With this information, we believed that it would be interesting to develop tools to analyze this subject of alterations and thus better understand the development of these pathologies.

2. What is the main advance?

The main advance is mainly in the methodology. Some existing algorithms do these analyses, but they do not use all the information available. With EventPointer, we use mathematical and statistical tools to combine all this information and generate a much more robust and complete analysis. We not only give values for statistical significance, but also means to visualize these disturbances.

 Currently, the research group continues to develop the algorithm and has included another tool that financial aid to experimentally validate all the splicing events detected by the algorithm.  

3. Will it have practical application?

The algorithm is available in one of the most important bioinformatics algorithms data instructions : Bioconductor. Since we uploaded it to this database, it has been downloaded more than 4 thousand times. We have also been cited in several scientific articles, demonstrating that academic community makes use of these tools in different research projects. Although it is true that, being a research algorithm, at the moment it is complicated to have a direct application on clinical cases. 

On the other hand, the algorithm is also part of the software of Affymetrix (company issue 1 in the world in microarrays). During a collaboration, we told them about the algorithm and they agreed to include it in their own software.

4. Why do you think you won the award Extraordinary Doctorate offered by Tecnun?

Maybe because what was done in the PhD became a real tool and available for everybody. I see my thesis as a contribution to the academic community in order to better understand the different diseases. On the other hand, I believe that, if I have had the opportunity to win this award, it is also thanks to the support of my thesis directors Dr. Ángel Rubio and Dr. Francis Planes. They helped me a lot on a day-to-day basis to better understand all the steps of the PhD and above all to prepare me for a future in the research field. I see it more as a award for the whole bioinformatics team at Tecnun.

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