Author

Iñigo Apaolaza

Universidad de NavarraORCID 0000-0002-8961-4513Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Organism:human· 4 Approach:statistical model· 4 Research Focus:gene regulatory network inference· 3 Assay:bulk RNA-seq· 2 Research Focus:differential expression· 2 Research Focus:drug response / drug discovery· 2 Research Focus:benchmarking· 1 Research Focus:database / resource· 1

Frequent Co-Authors

Francisco J. PlanesiD· 4 shared Edurne San José‐EneriziD· 2 shared Felipe PrósperiD· 2 shared Luis V. ValcárceliD· 2 shared Xabier AgirreiD· 2 shared Alberto M. Lerma-AguileraiD· 1 shared Alfonso ValenciaiD· 1 shared Ana Valcárcel· 1 shared

Activity by Year

2019-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 25 mutual co-author links

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4 shared papersSystems Biology

Francisco J. PlanesORCID

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4 papers

Recent·Most cited

gMCStool: automated network-based tool to search for metabolic vulnerabilities in cancer

Luis V. Valcárcel, Edurne San José‐Eneriz, Raquel Ordóñez, Iñigo Apaolaza, Ana Valcárcel, Leire Gárate, Jesús F. San Miguel, Antonio Pineda‐Lucena, Xabier Agirre, Felipe Prósper, Francisco J. Planes

gMCStool identifies metabolic vulnerabilities in cancer by predicting synthetic lethal interactions using genome-scale metabolic networks and RNA-seq data.

bioRxiv · Nov 3, 2022 · PreprintSystems Biology

A network-based approach to integrate nutrient environment in the prediction of synthetic lethality in cancer metabolism

Iñigo Apaolaza, Edurne San José‐Eneriz, Luis V. Valcárcel, Xabier Agirre, Felipe Prósper, Francisco J. Planes

This paper introduces a network-based method to predict synthetic lethality in cancer metabolism by integrating genetic interactions and nutrient environments, identifying potential vulnerabilities in tumor cells.

bioRxiv · Sep 1, 2021 · PreprintSystems Biology

An extended reconstruction of human gut microbiota metabolism for personalized nutrition

Telmo Blasco, Sergio Pérez-Burillo, Francesco Balzerani, Alberto M. Lerma-Aguilera, Daniel Hinojosa-Nogueira, Silvia Pastoriza, María José Gosalbes, Nuria Jiménez‐Hernández, Maria Pilar Francino, José Ángel Rufián‐Henares, Iñigo Apaolaza, Francisco J. Planes

This paper introduces AGREDA, an extended gut microbiota metabolism model for personalized nutrition, showing improved accuracy in predicting microbial output metabolites and identifying metabolic differences in Spanish children subgroups.

bioRxiv · Oct 23, 2020 · PreprintBioinformatics

On the inconsistent treatment of gene-protein-reaction rules in context-specific metabolic models

Miguel Ponce-de-León, Iñigo Apaolaza, Alfonso Valencia, Francisco J. Planes

The paper identifies common issues in how gene-protein-reaction (GPR) rules and gene expression data are handled in context-specific metabolic models and evaluates their impact on gene essentiality analysis.

Bioinformatics · Nov 12, 2019Peer-reviewedBioinformatics