Matteo Zambon

@mattezambon.bsky.social

PhD student @CRG.eu, Dias-Frazer Lab, Irimia Lab | Probabilistic Machine Learning and Computational Biology, Evolutionary Biology

How can we improve gene regulatory network inference from noisy scRNA-seq data? Our new review in @molsystbiol.org explores the latest methods integrating prior knowledge to enhance reliability. Plus, some suggestions on how to improve benchmarking! www.embopress.org/doi/full/10....

Leveraging prior knowledge to infer gene regulatory networks from single-cell RNA-sequencing data | Molecular Systems Biology

EMBO Press is an editorially independent publishing platform for the development of EMBO scientific publications.

embopress.org

Art and science merged this afternoon in a wonderful concert from our fellow PhD candidate Matilda Pfeiffer toghether with the musician Clara Cantore in a performance reflecting on points of contact between music and science. Couldn’t be more happy to be part of this phd community 💫 #CRGPhDSymp2024

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Attending a fascinating talk by Khashayar Baghizadeh on data-driven computational modeling of the Dentate Gyrus in Down Syndrome. Great work integrating anatomical and physiological data to unravel underlying mechanisms. #CRGPhDSymp2024

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As the #CRGPhDSymp progresses, Leo Zuber gave an insightful talk on his research integrating spatial information with GWAS data for developing a spatially aware, tissue-specific genomic risk score, evaluated in the context of COVID-19 disease severity. 🦠🧬

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Big 🧬 news this week: we have launched the first Joint Program on Evolutionary Medical Genomics. Spearheaded by @mirimiam.bsky.social, Barcelona researchers will study and exploit the vast genomic diversity of life on Earth to enhance precision medicine. Full story in @elpais.com

The dawn of a new medicine: Researchers use the theory of evolution to fight cancer

The world’s first joint research program in evolutionary medical genomics has been launched in Barcelona, under the direction of biologist Manuel Irimia

english.elpais.com