Recent & Upcoming Talks

2020

POMA: An User-friendly Workflow for Pre-processing and Statistical Analysis of Mass Spectrometry Data

Dec 18, 2020 12:00 AM Virtual Conference
Code Slides

FOBI: An ontology to represent food intake data and associate it with metabolomic data

Nutrition research can be conducted by using two complementary approaches: (i) traditional self-reporting methods or (ii) via metabolomics techniques to analyze food intake biomarkers in biofluids. However, the complexity and heterogeneity of these two very different types of data often hinder their analysis and integration.
Oct 27, 2020 12:00 AM Virtual Conference
Code

POMAShiny: An User-friendly Web-based Workflow for Statistical Analysis of Mass Spectrometry Data

Mass spectrometry, like other high-throughput technologies, usually faces a data mining challenge to provide an understandable output to advance in biomarker discovery and precision medicine. Often, statistical analysis is one of the hard points and it’s critical in the subsequent biological interpretation of the results.
Oct 15, 2020 12:00 AM Virtual Conference
Code Slides

FOBI: An ontology to represent food intake data and associate it with metabolomic data

Nutrition research can be conducted by using two complementary approaches: (i) traditional self-reporting methods or (ii) via metabolomics techniques to analyze food intake biomarkers in biofluids. However, the complexity and heterogeneity of these two very different types of data often hinder their analysis and integration.
Sep 23, 2020 12:00 AM Virtual Conference
Code Slides

FOBI: An ontology to represent food intake data and associate it with metabolomic data

Nutrition research can be conducted by using two complementary approaches: 1) traditional self-reporting methods or 2) via metabolomics techniques to analyze food intake biomarkers in biofluids. However, the complexity and heterogeneity of these two very different types of data often hinder their analysis and integration.
Jan 22, 2020 12:00 AM Toulouse, France
Code

2019

FOBI: An ontology to represent food intake data and associate it with metabolomic data

Nutrition research can be conducted by using two complementary approaches: 1) traditional self-reporting methods or 2) via metabolomics techniques to analyze food intake biomarkers in biofluids. However, the complexity and heterogeneity of these two very different types of data often hinder their analysis and integration.
Dec 17, 2019 12:00 AM Barcelona, Spain
Code

POMA: Shiny Framework Statistical analysis tool for targeted metabolomic data

Similarly to other high-throughput technologies, metabolomics usually faces a data mining challenge to provide an understandable and useful output to advance in biomarker discovery and precision medicine. Biological interpretation of the results is one of the hard points and several bioinformatics tools have emerged to simplify and improve this step.
Jul 11, 2019 12:00 AM Toulouse, France
Code Slides

POMA: Shiny Framework Statistical analysis tool for targeted metabolomic data

Similarly to other high-throughput technologies, metabolomics usually faces a data mining challenge to provide an understandable and useful output to advance in biomarker discovery and precision medicine. Biological interpretation of the results is one of the hard points and several bioinformatics tools have emerged to simplify and improve this step.
Jan 25, 2019 12:00 AM Santiago de Compostela, Spain
Code

Epigenome-wide association study in Childhood Obesity: Searching for early markers of late disease risk

Rationale: Childhood obesity is one a major Public Health issue. Overweight/obese children have a high risk of being obese as adults and develop other co-morbidities, including type 2 diabetes, cardiovascular disease and several types of cancer.
Jan 16, 2019 12:00 AM Cambridge, UK