Martí-Franquès COFUND Fellowship Programme


Details

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Reference:

2018MFP-COFUND-4

Area:

Engineering and Architecture

Supervisor name and surname:

Jesus Brezmes Llecha

Supervisor email:

jesus.brezmes@urv.cat

Supervisor short biography

Co-supervisor name and surname:

Nicolau Cañellas Alberich

Co-supervisor email:

nicolau.canellas@urv.cat

Co-supervisor institution:

Universitat Rovira i Virgili

Co-supervisor short biography

PhD programme:

Technologies for Nanosystems, Bioengineering and Energy

Title of the research project:

Data processing and analysis for metabolomic studies

Description of the research project:

Personalized medicine has been touted as the future of healthcare. Individualized treatments are required for different patients according to their different traits."Omic" sciences are one of the areas were more researchers are trying to find the information to make this vision true. Inside the "Omics" term, Genomics, Transcriptomics, Proteomics and Metabolomics are the main branches of this philosophy.

Although all four branches of research are important, probably the latest to join the group is the one that has more options to become a mainstream area of research and innovation. The reason for this is three-way: First, while Genomics can tell you what might happen due to your genotype, metabolomics tells you what is actually happening knowing your phenotype. Secondly, metabolomics is the result of intrinsic genotypes but also is greatly affected by external factors which, of course, are also taken. Finally, since external factors affect the metabolome, more actions can be taken to improve the overall health of a patient.

Nowadays, technical advances have generated a large amount of measurement techniques that can be used to detect, identify and quantify metabolites (small molecules present mainly in biofluids or tissues of living entities like humans). One common characteristic of these systems is the wealth of raw data they generate for each measurement. Converting this raw data into useful metabolomic and clinical information is key to find exciting new applications of these techniques towards the Personalized Medicine envisaged for the 21st century.

The goal of the project is to devise algorithms in the fields of biostatistics, digital signal processing, pattern recognition, multivariate analysis and neural networks to be able to process raw data coming from the measuring of biofluids such as serum, plasma or urine with different stablished techniques like NMR, Gas/liquid Chromatography-MS and MALDI-TOF to add relevant clinical information to the metabolomics field. The research group is in touch with many medical teams and has access to state-of-the-art instruments that provide the most advanced characteristics (sensitivity, selectivity, automation, data acquisition handling and storing raw data, etc.).

All these algorithms will be developed in open platforms such as R, the gold standard for statistical analysis in biosciences, and will be validated with real samples and real problems that have not been solved until now. We are involved with the Ciberdem institute that can provide all the samples and cases to study and the Institut Pere i Virgili de recerca. Metabolomics and the techniques that provide the information needed have a bright future in medicine, since the information obtained can be used for early diagnosis through the discovery of robust and significant biomarkers or to assess the efficacy of new treatments. All this work could be included in a new profile of researchers commonly known as "data scientists".

Gross anual salary:

26443.80 €

Dedication:

Full time

Working hours:

37.5 hours a week

Expected start date:

European union This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 713679