Author

Alejandro Corrochano-Navarro

Sanofi (United States)

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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Bioinformatics· 1 Molecular Biology· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 1 Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Approach:experimental assay· 1 Approach:machine learning (classical)· 1 Assay:protein structure· 1 Research Focus:protein structure prediction· 1

Frequent Co-Authors

Lorenzo Kogler-Anele· 2 shared Michael BaileyiD· 2 shared Ruijiang LiiD· 2 shared Sven JägeriD· 2 shared Ziv Bar‐JosephiD· 2 shared Abhinav GuptaiD· 1 shared Alexander KötteriD· 1 shared Christoph GrebneriD· 1 shared

Activity by Year

2023-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 41 mutual co-author links

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2 shared papersMolecular Biology

Lorenzo Kogler-Anele

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2 papers

Recent·Most cited

Active Learning for Protein Structure Prediction

Zexin Xue, Michael Bailey, Abhinav Gupta, Ruijiang Li, Alejandro Corrochano-Navarro, Sizhen Li, Lorenzo Kogler-Anele, Qian Yu, Ziv Bar‐Joseph, Sven Jäger

The paper applies a novel active learning strategy, DEW-DROP, to improve protein structure prediction efficiency and data selection for two protein datasets.

Lecture notes in computer science · Jan 1, 2025Peer-reviewedMolecular Biology

Deep Batch Active Learning for Drug Discovery

Michael Bailey, Saeed Moayedpour, Ruijiang Li, Alejandro Corrochano-Navarro, Alexander Kötter, Lorenzo Kogler-Anele, Saleh Riahi, Christoph Grebner, Gerhard Heßler, Hans Matter, Marc Bianciotto, Pablo Mas, Ziv Bar‐Joseph, Sven Jäger

The paper develops two novel active learning batch selection methods for drug discovery, showing significant improvements over existing methods across multiple datasets.

bioRxiv · Jul 26, 2023 · PreprintBioinformatics