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Categoría: Journal Club
16/11/2022 - Journal Club
New to machine learning in proteomics? Check out the ‘ProteomicsML’ web platform
Machine learning approaches have become an established part of the mass spectrometry-based proteomics field in recent years. Several tools capable of predicting different aspects of peptide behavior have been developed and incorporated in data analysis workflows. These tools have proven to be beneficial in peptide and protein identification in proteomics experiments, and it is therefore […]
26/06/2022 - Journal Club
“Cross-Linking Mass Spectrometry: A sneak peak into its world!! ”
It has been a while since our official PROTrEIN launch. We’ve had monthly ESR meetings during this time, where the majority of us have been able to discuss more details about our projects and present them to the group. Several ESRs are working on developing new tools and data analysis pipelines to improve cross linking […]
20/05/2022 - Journal Club
A Systematic Review on Bioethics in Proteomics
The moment to begin exercising control over the rules and regulations that will bind us tomorrow is soon. The time to begin thinking and talking about them is now. In this month’s Journal Club, we have decided to step away from technical topics such the latest advances in proteomics methodologies. Instead, we will approach a more “philosophic” […]
15/04/2022 - Journal Club
Adding the third dimension to protein modifications analysis
Short description In the study of post-translational modifications from mass spectrometry experiments, proteins are almost always represented as a linear string of amino acids. However, it should be kept in mind that proteins’ function is conferred by their 3-dimensional structure and that understanding the modifications of proteins calls for studying them in their structural context. […]
28/03/2022 - Journal Club
Machine Learning Algorithms Applications in fMRI Data Analysis
The article Performance of machine learning classification models of autism using resting-state fMRI is contingent on sample heterogeneity (Maya A. Reiter, Afrooz Jahedi, A. R. Jac Fredo, Inna Fishman, Barbara Bailey, Ralph-Axel Müller, Springer Nature 2020) was chosen because it shows potential applications of machine learning in fMRI data analysis. Unsupervised machine learning has been […]
17/02/2022 - Journal Club
How to train your modified peptide MS/MS spectrum predictor?
This month’s PROTrEIN journal club covers an article presenting a tool – pDeep2 – capable of predicting MS/MS spectra of modified peptides.1 pDeep2 is built using a machine learning technique that makes it possible to generate prediction even when there are only a few datasets available for training the model. But… What is this machine learning […]
31/01/2022 - Journal Club
Ion mobility meets Deep Learning.
Proteomics can be simply defined as the large-scale analysis of proteins – all the meaningful genome products – in a given sample [1,2]. Mass spectrometry (MS)-based proteomics is one of the most powerful approaches for identifying proteins from biological samples. Over years, there were many proteomics workflows generated by scientists in this field. The development […]
14/12/2021 - Journal Club
How to choose a proper combination of search engines to maximize Peptide and Protein Identification?
In this Journal Club, our ESRs Zahra and Arslan present the article «Optimization of Search Engines and Postprocessing Approaches to Maximize Peptide and Protein Identification for High-Resolution Mass Data» by C. Tu et al. from Sep 2015
14/10/2021 - Journal Club
How can proteomics data become more reproducible?
In this Journal Club, our ESRs Louise and Shamil present the article «Strategies to enable large-scale proteomics for reproducible research» by R. Poulos et al. from July 2020