Oscar Yanes
@yaneslab
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Biochemist. Coordinator @ciberdem @IISPereVirgili #Metabolomics Platform. Assistant Prof @etseURV. Affiliated member @IRBBarcelona. Former @scrippsresearch
Tarragona, Catalonia
Joined November 2011
We’re excited to share our latest work "Improving MALDI Mass Spectrometry Imaging Performance: Low-Temperature Thermal Evaporation for Controlled Matrix Deposition and Improved Image Quality" | Journal of the American Society for Mass Spectrometry https://t.co/osES2hkvFD 🧵👇
pubs.acs.org
The deposition of matrix compounds significantly influences the effectiveness of matrix-assisted laser desorption/ionization (MALDI) Mass Spectrometry Imaging (MSI) experiments, impacting sensitivi...
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Delighted and honored to have participated in this fascinating study led by @ManelEsteller
Excited to share our #multiomics study of who was the world's #oldest living person! Our research on this record-breaking #supercentenarian suggests that, under certain conditions, #aging and #disease can become decoupled—challenging the common belief that they are inherently
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ONLY 3 DAYS LEFT for computational biologists ...! To apply for a PhD position - on Metabolic Genome Regulation - in Acute Myeloid Leukemia - supervised by @tvavouri and me - at @carrerasIJC - in Barcelona, Spain - part of @MSCActions HubMOL https://t.co/CKPH0Snhhg Please RT!
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5/ Want to learn more? 📄 Read our full paper on #bioRxiv: https://t.co/0HdEuHz89h
#Metabolomics #MachineLearning #DeepLearning #MSMS We’d love to hear your thoughts! This is another successful collaboration with @sees_lab at @universitatURV
biorxiv.org
Machine learning tools have become essential for annotating the vast number of unidentified MS/MS spectra in metabolomics, addressing the limitations of current reference spectral libraries. However,...
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3/ We enhance MS/MS data by: ✅ Merging spectra from multiple collision energies ✅ Incorporating calculated neutral losses ✅ Training a CNN on a dataset of 38,472 unique compounds from NIST20, MSDIAL, GNPS, and Agilent METLIN metabolomic libraries.
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2/ Our solution: #ChemEmbed. We combine enhanced MS/MS spectra with continuous vector representations of molecular structures (300-dimensional embeddings aligned with Mol2vec representations). This gives our CNN-based model richer input, improving annotation accuracy.
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1/ The problem: #Metabolomics relies on MS/MS spectral databases, but most spectra remain unidentified due to limited reference libraries. Computational methods help, but they struggle with high-dimensional and sparse spectral and structural data.
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🚀 New paper alert! 🚀 Happy to introduce #ChemEmbed, a deep learning framework for metabolite identification that enhances MS/MS data and leverages multidimensional molecular embeddings. A 🧵 on how it works ⬇️ #metabolomics #MachineLearning #DeepLearning
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I finally moved to #BlueSky #BlueskySocial Kind of funny to add this in X, but I'll end up quitting this platform. Here's my profile in BlueSky for those interested :
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An ongoing study in our lab focuses on developing new matrices for MALDI-MSI of small molecules (m/z <400) using LTE deposition. We're minimizing matrix background interference while enhancing metabolite ionization and coverage, paving the way for #Spatial #Metabolomics
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🔬 Read more about how LTE advances the field of MALDI-MSI, including crystal morphology, stability tests, and comparative analysis with spray-coating, in our new preprint: https://t.co/Ru9MXUsnZG
#MALDIMS #MassSpectrometry #Lipidomics
biorxiv.org
The deposition of matrix compounds significantly influences the effectiveness of matrix-assisted laser desorption/ionization (MALDI) Mass Spectrometry Imaging (MSI) experiments, impacting sensitivi...
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Spray-coating is the most popular method, but LTE outperforms it by: 🔹 Enhancing ionization efficiency 🔹 Reducing analyte diffusion 🔹 Improving spatial resolution & image quality in MSI images
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Stability is another win! After storing mouse brain sections coated with DHB or DAN matrices at -80 °C for two weeks, ionization efficiency, signal intensity, and image quality remained consistent. Robustness is crucial for long-term studies, and LTE delivers! 💪
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Our LTE deposition method works under reduced vacuum pressure, enabling precise control over matrix thickness. With linear calibrations for DHB & DAN, LTE ensures a reproducible matrix layer thickness—critical for consistent results!
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💡 Why focus on matrix deposition? It’s a key factor in MALDI-MSI experiments, influencing data quality, analyte localization, and experimental reproducibility. Traditional methods have limitations, so we aimed to improve the game.
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I am thrilled to finally share our work on persister cancer cells: we identify distinctive features and actionable #vulnerabilities ⚡️of persister cancer cells (#DTP), and provide mechanistic insight into their low #inflammatory activity: https://t.co/hf5gHbmtq0 👩🔬🧪🔎 ⬇️
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Mai oblidaré el teu bon tracte i la confiança que vas dipositar en mi. Joan, sempre t'estaré agraït. DEP 🫶🏼
Amb profunda tristesa, lamentem comunicar la mort aquesta passada matinada del Dr. Joan Guinovart, fundador, exdirector, exinvestigador i professor emèrit de l’IRB Barcelona. El Dr. Guinovart ha estat una figura clau en l’àmbit de la bioquímica, deixant una empremta
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