Author

Pedro Febrer Martinez

University of GenevaORCID 0009-0007-0627-1871Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Signature Assays, Organisms & Methods

Click to filter · or open tag

Research Focus:benchmarking· 1 Research Focus:database / resource· 1 Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Assay:protein structure· 1 Approach:statistical model· 1

Frequent Co-Authors

Francesco Luigi GervasioiD· 2 shared Alberto BorsattoiD· 1 shared Antonija KuzmaniciD· 1 shared Simone AureliiD· 1 shared Thorben FröhlkingiD· 1 shared Valerio RizziiD· 1 shared Vladimiras OleinikovasiD· 1 shared

Activity by Year

2024-2026 · peak 1/yr

Co-Author Collaboration Network

7 top collaborators · 13 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

2 shared papersBioinformatics

Francesco Luigi GervasioORCID

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

BioinformaticsScience AdvancesPeer-reviewedApr 22, 2026

CryptoBank: A Resource for the Identification and Prediction of Cryptic Sites in Proteins

Pedro Febrer Martinez, Thorben Fröhlking, Alberto Borsatto…·Francesco Luigi Gervasio

CryptoBank identifies cryptic binding sites in proteins using structural alignments and a machine learning model, enabling prediction from sequence data with high precision.

5 citationstop 1%

humanprotein structure

𝕏 PostBluesky

BiochemistryJournal of Chemical Theory and ComputationPeer-reviewedNov 14, 2024

Host-Guest binding free energies a la carte: an automated OneOPES protocol

Pedro Febrer Martinez, Valerio Rizzi, Simone Aureli, Francesco Luigi Gervasio

This paper introduces an automated OneOPES protocol to improve binding free energy estimation in host-guest systems by enhancing sampling and enabling systematic force field comparison.

9 citations

deep learningstatistical model

𝕏 PostBluesky