Author

Daniel Aguilera

Consejo Nacional de Investigaciones Científicas y Técnicas

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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Neuroscience· 1 Synthetic Biology· 1

Signature Assays, Organisms & Methods

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Research Focus:dimensionality reduction· 1 Organism:human· 1 Assay:imaging· 1 Approach:machine learning (classical)· 1 Research Focus:protein design· 1 Assay:protein sequence· 1 Approach:statistical model· 1 Organism:yeast· 1

Frequent Co-Authors

Aditya Udupa· 1 shared Angelica W. Y. Lam· 1 shared Christopher TimmermanniD· 1 shared Claire J. LeBlanc· 1 shared Dante Sebastián Galván RialiD· 1 shared Emmanuel Andreas StamatakisiD· 1 shared Gabriel A. Della BellaiD· 1 shared Gean Hu· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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1 shared paperSynthetic Biology

Aditya Udupa

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

Machine learning guided design of strong transcriptional activation domains

Marissa A. Zintel, Claire J. LeBlanc, Sanjana R. Kotha, Melvin Soriano, Rishaan J. Bansal, Daniel Aguilera, Touss Majidi, Izaiah Ornelas, Liam D. Kirkpatrick, Aditya Udupa, Gean Hu, Pooja Agarwal, Angelica W. Y. Lam, James K. Nunez, Patrick M. Shih, , Max V. Staller

The paper designs functional transcriptional activation domains using machine learning and experimental validation, finding that over 90% of predicted sequences work in yeast.

bioRxiv · Nov 2, 2026 · PreprintSynthetic Biology

A Shared Entropic Axis Spans States of Consciousness Across Pharmacological and Clinical Conditions

Dante Sebastián Galván Rial, Gabriel A. Della Bella, Lorina Naçi, Stefano Delli Pizzi, Stefano L. Sensi, Tristán M. Osán, Daniel Aguilera, Christopher Timmermann, Robin Lester Carhart-Harris, Emmanuel Andreas Stamatakis, Pablo Barttfeld

The paper quantifies consciousness states using entropy across pharmacological and clinical fMRI data, finding a shared entropic axis spanning from low-entropy anaesthesia to high-entropy psychedelic and schizophrenia states.

bioRxiv · Jun 16, 2026 · PreprintNeuroscience