Francesco Strozzi
fstrozzi.bsky.social
Francesco Strozzi
@fstrozzi.bsky.social
Passionate about Science, Bioinformatics, Healthcare and Data.

I’m an Elder Millennial
Reposted by Francesco Strozzi
New Journal for ImmunoTherapy of Cancer ( #JITC ) article: Mimicry-based strategy between human and commensal antigens for the development of a new family of immune therapies for cancer bit.ly/3ET6xtD @fstrozzi.bsky.social @wickwolfgang.bsky.social
February 25, 2025 at 2:40 PM
Reposted by Francesco Strozzi
This is an amazing technology, we are already using it ourselves and it is transformative. Kudus to @caleblareau.bsky.social and @ronanchaligne.bsky.social and their teams.
January 9, 2025 at 6:57 PM
Reposted by Francesco Strozzi
Some thoughts about what I am looking forward this year from my vantage point of computational molecular biology. One mega-trend for me; we will definitely see more AI methods of all sorts emerge.
January 3, 2025 at 6:46 PM
Reposted by Francesco Strozzi
CASSIA allows for robust, automated cell annotation in single-cell RNA-sequencing data https://www.biorxiv.org/content/10.1101/2024.12.04.626476v1
December 9, 2024 at 4:01 AM
Reposted by Francesco Strozzi
Great collaboration with @itisalist.bsky.social

We hope our study and set of tools and resources can be helpful to the scientific community 💫

📝 preprint: doi.org/10.1101/2024...
🛠️ omnideconv ecosystem: omnideconv.org

Please repost and help us spread the word!

6/6
Benchmarking second-generation methods for cell-type deconvolution of transcriptomic data
In silico cell-type deconvolution from bulk transcriptomics data is a powerful technique to gain insights into the cellular composition of complex tissues. While first-generation methods used precompu...
doi.org
November 12, 2024 at 1:41 PM
Digital profiling of gene expression from histology images with linearized attention.

Codes for data pre-processing, model training and evaluation are available on GitHub: github.com/gevaertlab/s...

www.nature.com/articles/s41...
Digital profiling of gene expression from histology images with linearized attention - Nature Communications
Predicting gene alterations and expression from whole-slide images (WSIs) can be a cost-efficient solution for cancer profiling. Here, the authors develop SEQUOIA, a transformer model with linearised ...
www.nature.com
November 25, 2024 at 5:55 AM
Reposted by Francesco Strozzi
Atlas of the plasma proteome in health and disease in 53,026 adults 👩‍🔬🥼👨‍🔬🧪. #proteomics #proteome #plasma #MedSky 👇👇

www.cell.com/cell/fulltex...
Atlas of the plasma proteome in health and disease in 53,026 adults
A large-scale proteomics study involving 53,026 individuals maps 2,920 plasma proteins to 406 prevalent diseases, 660 incident diseases, and 986 health-related traits, identifying promising biomarkers...
www.cell.com
November 23, 2024 at 7:49 AM