Author

Sebastian Ibarraran

Stanford University

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

Biology Disciplines

Click to filter author papers

Bioengineering· 1 Bioinformatics· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Approach:deep learning· 2 Assay:protein sequence· 2 Research Focus:protein design· 1 Research Focus:software / tool· 1 Approach:statistical model· 1

Frequent Co-Authors

Frank HuiD· 2 shared Grant M. RotskoffiD· 2 shared Abigail ParkiD· 1 shared Alexander R. DunniD· 1 shared Jason Liu· 1 shared Shriram ChennakesavaluiD· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

6 top collaborators · 12 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 papersBioengineering

Frank HuORCID

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

Efficient, Few-shot Directed Evolution with Energy Rank Alignment

Sebastian Ibarraran, Shriram Chennakesavalu, Frank Hu, Grant M. Rotskoff

This paper introduces a method to improve protein engineering efficiency using pre-trained protein language models and statistical physics-based post-training to generate high fitness sequences with fewer experimental data points.

Journal of Chemical Information and Modeling · Aug 26, 2026Peer-reviewedBioengineering

Generative design of intrinsically disordered protein regions with IDiom

Jason Liu, Sebastian Ibarraran, Frank Hu, Abigail Park, Alexander R. Dunn, Grant M. Rotskoff

The paper introduces IDiom, a language model for generating intrinsically disordered protein sequences, showing it can produce sequences with biologically relevant features and subcellular localization properties.

bioRxiv · Apr 11, 2026 · PreprintBioinformatics