Sunday 12:45–13:30 in Novice - 2

LympHOS2, Organizing and Sharing Biological Data of the Human Lymphocyte Proteome using Python

Óscar Gallardo Román

Audience level:


The study of the proteome (the set of proteins expressed by a cell, tissue, or organism at a defined time and conditions) generates a large amount of complex data. This data should be processed, stored, curated, and made easily available to researchers so it can be studied to obtain biomedical knowledge. In this talk we expose the Python tools we have used and developed to accomplish it.


At the LP-CSIC/UAB we use a technology called Mass Spectrometry to study the phospho-proteome of human T-Lymphocytes; this is, the group of proteins that are phosphorilated (modified with phosphate groups) in the human T cells during their activation and differentiation as part of the immune response. The experiments involved in this study generates a large amount of complex data:

And all this data has to be processed, stored, curated, and made easily accessible to researchers in our lab and worldwide, so they can study it to obtain biomedical knowledge about the phosphorylation changes in peptides and proteins involved in the signal transduction pathways of T cells after their activation during the specific immune response.

We have used different Python packages to develop different tools and applications to accomplish those objectives:

The final result is the LymPHOS2 web-oriented database, that nowadays (2017) contains 131.908 mass spectra, 15.566 phosphorylation sites from 8.273 unique phospho-peptides and 4.937 proteins (which represent a 45-fold increase over the original LymPHOS database of 2009); aside from the new quantitative data for 1.975 of the identified phospho-peptides, which was not present in the previous version of LymPHOS.

Repositories and Presentation Slides:


The exposed work has been carried out at LP-CSIC/UAB from Catalonia, part of the Spanish National Research Council (Consejo Superior de Investigaciones Científicas - CSIC) and of ProteoRed (Proteomics National NetWork Platform).

The people who have participated directly in the current work are:

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