Skip to main content
Pedro Beltrao on Muck Rack

Pedro Beltrao

Zürich
As seen in: Nature, Wiley Online Library, Science Magazine, BioRxiv, Cell Press, Cell Reports, CNN Brasil
Associate professor at ETH (@IMSB_ETH) studying the cellular consequences of genetic variation. Part of @theLoopZurich.
Is this you? As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work. Claim your profile

Get in touch with Pedro

Contact Pedro, search articles and posts on X, monitor coverage, and track replies from one place.

Learn more about Muck Rack

Actions

Share this page

Is this you?

As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work.
Claim your profile

Articles

The PRECISE European initiative for cancer-vulnerability mapping and prediction

|
By Francesco Iorio, Mathew J Garnett, Pedro Beltrao, Maximilian Billmann, Larissa Bless, Christoph Bock, Michael Boutros, Alejandra Bruna, Piero Carninci, Giovanni Ciriello, Isidro Cortes-Ciriano, Giuseppina D’Alessandro, Roberta Esposito, Stefania Faletti, Emanuel Gonçalves, Syed Imran Haider, Nereo Kalebic, Manuel Kaulich, Giuseppe Leuzzi, Nuria Lopez-Bigas, Christopher Lord Verified, Evangelia Petsalaki, Stephen Pettitt, Ludovica Proietti, Roland Rad, Colm J. Ryan, Jonathan L. Schmid-Burgk, Sumana Sharma, Andrea Sottoriva, Christopher J. Tape, Livio Trusolino, Jolanda van Leeuwen, David Walter, Lodewyk Wessels, Nevenka Radic
| Nature Verified
PRECISE is a European initiative to move cancer research beyond descriptive atlases toward predictive, mechanistically informed models of tumor vulnerability. By integrating patient cohorts, disease-relevant model systems, perturbation biology, multimodal profiling and artificial intelligence-driven inference, the PRECISE consortium aims to learn generalizable and predictive rules that govern genetic dependencies and synthetic lethality.
Open in Who Shared Issue with article?

The AlphaGenome deep learning model predicts effects of non-coding variants - Nature Structural & Molecular Biology

|
By Dennis Gankin, Pedro Beltrao
| Nature Verified
Google’s DeepMind presents AlphaGenome, the largest multimodal DNA sequence model for non-coding regions so far. It advances the state of the art in almost all prediction tasks and offers a new unified tool to study the effects of genomic variation on regulatory cellular mechanisms. However, opportunities for further improvement remain.
Open in Who Shared Issue with article?

Structure and assembly of the A-C linker connecting microtubule triplets in centrioles

|
By Sarang Mahajan, Ala’a Al Hrout, Erik H. Collet, Haiping Xiong, Bin Cai, Ellen Aarts, Leo Luo, Alexander Leitner, Takashi Ishikawa, Pedro Beltrao, Chad G. Pearson, Martin Pilhofer, Michal Wieczorek
| Science Magazine Verified
Abstract Centriole assembly involves the coordination of centriolar modules. One module is the A-C linker, an enigmatic protein assembly connecting the A-microtubule of one microtubule triplet to the C-microtubule of the neighboring triplet. Here, we integrated biochemistry, multiscale cryo–electron microscopy, and AlphaFold modeling to investigate the architecture of the centriole.
Open in Who Shared Issue with article?
See all 15 articles