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Guillermo Prol-Castelo

@gprolcastelo.bsky.social
39 followers 74 following 23 posts

Bioinformatics predoctoral researcher at @bsc-cns.bsky.social and @upf.edu #AI #bio github.com/gprolcastelo

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Guillermo Prol-Castelo @gprolcastelo.bsky.social · 04/05/2026
our systematic literature reviewper on deep learning for modeling cancer over time just published open access in Briefings in Bioinformatics! shared a preprint summary here last year—peer review really improved it; if you're into cancer AI or temporal modeling, read it here: doi.org/10.1093/bib/...
doi.org
Deep representation learning for temporal inference in cancer omics: a systematic literature review
Abstract. Deep learning methods, including deep representation learning (DRL) approaches such as variational autoencoders (VAEs), have been widely applied
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BSC-CNS @bsc-cns.bsky.social · 27/11/2025
🤖 Torna la #BitsxlaMarató! I ja van 7 edicions col·laborant amb #LaMarató3CAT 💻 El BSC és un dels organitzadors d’aquesta hackathon, que aquest any compta amb la col·laboració de l'Institut Català d'Oncologia.
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More Perfect Union @moreperfectunion.bsky.social · 04/11/2025
OpenAI pirated large numbers of books and used them to train models. OpenAI then deleted the dataset with the pirated books, and employees sent each other messages about doing so. A lawsuit could now force the company to pay $150,000 per book, adding up to billions in damages.
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Reposted by Guillermo Prol-Castelo
EvenFlow Project @evenflowproject.bsky.social · 19/06/2025
🎉 Congratulations to EVENFLOW partner @gprolcastelo.bsky.social on the publication of his second PhD pre-print! 📄 A contribution to understanding VAEs in cancer progression research, supported by the @evenflowproject.bsky.social project. Learn more 👇 #CancerResearch #DeepLearning
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Guillermo Prol-Castelo @gprolcastelo.bsky.social · 12/06/2025
New research alert 📝❗❗❗ In our latest pre-print, 2nd of my PhD, we performed a Systematic Literature Review on the use of Deep Representational Learning (DRL), especially the Variational Autoencoder (VAE), in cancer progression research. This thread explains our main findings. (1 minute read)
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bioRxivpreprint @biorxivpreprint.bsky.social · 05/06/2025
10 Years of Variational Autoencoder: Insights from Cancer Temporal Progression Studies, a Systematic Literature Review www.biorxiv.org/content/10.1101/202…
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Reposted by Guillermo Prol-Castelo
AI x Bio Discovery @aixbiobot.bsky.social · 05/06/2025
10 Years of Variational Autoencoder: Insights from Cancer Temporal Progression Studies, a Systematic Literature Review [new] VAE cancer omics analysis reveals temporal modeling gap (limited data). Proposes VAEs for cancer staging.
10 Years of Variational Autoencoder: Insights from Cancer Temporal Progression Studies, a Systematic Literature ReviewFigure 1Figure 2Figure 3
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bioRxiv Bioinfo @biorxiv-bioinfo.bsky.social · 05/06/2025
10 Years of Variational Autoencoder: Insights from Cancer Temporal Progression Studies, a Systematic Literature Review www.biorxiv.org/content/10.1101/202…
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Reposted by Guillermo Prol-Castelo
Alfonso Valencia @alfonsovalencia.bsky.social · 13/01/2025
Happy to be part of the amazing new world of synthetic data by the hand of @gprolcastelo.bsky.social in Davide Cirillo’s group!!
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Guillermo Prol-Castelo @gprolcastelo.bsky.social · 13/01/2025
New Insights into Medulloblastoma! 🧠 I am very happy to announce the first paper in my Ph.D. thesis journey: Exploring the Boundaries of Medulloblastoma Subgroups with synthetic Data Generation -> www.biorxiv.org/content/10.1... Let’s dive in into our findings with this thread! 🧵⤵️
biorxiv.org
Exploring the Boundaries of Medulloblastoma Subgroups with Synthetic Data Generation
Medulloblastoma is a childhood brain tumor traditionally classified into four molecular subgroups. Recent evidence suggests that Groups 3 and 4 represent a biological continuum rather than distinct en...
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AI x Bio Discovery @aixbiobot.bsky.social · 02/01/2025
Exploring the Boundaries of Medulloblastoma Subgroups with Synthetic Data Generation [new] Explores subgroups by generating synthetic transcriptomics data with a VAE, supporting a continuum between groups 3 and 4.
Exploring the Boundaries of Medulloblastoma Subgroups with Synthetic Data GenerationFigure 1Figure 2Figure 3
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bioRxivpreprint @biorxivpreprint.bsky.social · 30/12/2024
Exploring the Boundaries of Medulloblastoma Subgroups with Synthetic Data Generation www.biorxiv.org/content/10.1101/202…
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