Author

P. Aloy

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Cancer Biology· 2 Biochemistry· 1 Cell Biology· 1

Signature Assays, Organisms & Methods

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Approach:experimental assay· 3 Approach:deep learning· 2 Research Focus:drug response / drug discovery· 2 Organism:human· 2 Assay:bulk RNA-seq· 1 Research Focus:cell signaling & trafficking· 1 Research Focus:cell type annotation· 1 Research Focus:clustering· 1

Frequent Co-Authors

L. Mateo· 2 shared M. Duran-Frigola· 2 shared A. Califano· 1 shared A. Fernandez· 1 shared A. Fernandez-Torras· 1 shared A. Gris-Oliver· 1 shared A. Pessia· 1 shared A. R. Nebreda· 1 shared

Activity by Year

2019-2022 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 15 mutual co-author links

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2 shared papersCancer Biology

L. Mateo

Mutual co-authors in cluster

Author profile →

4 papers

Recent·Most cited

Characterization of p38a signaling networks in cancer cells using quantitative proteomics and phosphoproteomics

Y. Dan, N. Radic, M. Gay, A. Fernandez, G. Arauz, M. Vilaseca, P. Aloy, B. Canovas, A. R. Nebreda

This study identifies p38-regulated proteins and phosphoproteins in breast cancer cells, revealing its role in cell adhesion, DNA replication, and RNA metabolism.

bioRxiv · Sep 9, 2022Biochemistry

A Community Challenge for Pancancer Drug Mechanism of Action Inference from Perturbational Profile Data

E. F. Douglass, R. J. Allaway, B. Szalai, W. Wang, T. Tian, A. Fernandez-Torras, R. Realubit, C. Karan, S. Zheng, A. Pessia, Z. Tanoli, M. Jafari, F. Wan, S. Li, Y. Xiong, , A. Califano

The paper hosts a DREAM Challenge to evaluate computational models for predicting drug polypharmacology using perturbational profile data from 32 kinase inhibitors.

bioRxiv · Dec 21, 2020Cancer Biology

Personalized Cancer Therapy Prioritization Based on Driver Alteration Co-occurrence Patterns

L. Mateo, M. Duran-Frigola, A. Gris-Oliver, M. Palafox, M. Scaltriti, P. Razavi, S. Chandarlapaty, J. Arribas, M. Bellet, V. Serra, P. Aloy

The paper identifies actionable genomic vulnerabilities in cancer by analyzing driver alteration co-occurrence patterns and validates predictions in mice, improving drug response modeling from patient data.

bioRxiv · Sep 18, 2020Cancer Biology

Exploring endocytic compartment morphology with systematic genetics and single cell image analysis

M. Mattiazzi Usaj, N. Sahin, H. Friesen, C. Pons, M. Usaj, M. Paz Masinas, E. Shuteriqi, A. Shkurin, P. Aloy, Q. Morris, C. Boone, B. J. Andrews

The paper uses systematic genetics and single-cell image analysis to identify genes affecting endocytic compartment morphology in yeast, revealing pleiotropy and cellular heterogeneity.

bioRxiv · Aug 4, 2019Cell Biology