🎉 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

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)

10 Years of Variational Autoencoder: Insights from Cancer Temporal Progression Studies, a Systematic Literature Review https://www.biorxiv.org/content/10.1101/2025.05.29.656750v1

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 Review https://www.biorxiv.org/content/10.1101/2025.05.29.656750v1

Happy to be part of the amazing new world of synthetic data by the hand of @gprolcastelo.bsky.social in Davide Cirillo’s group!!

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! 🧵⤵️

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 Generation https://www.biorxiv.org/content/10.1101/2024.12.30.630738v1