Author

Jacob Rodriguez

University of WashingtonORCID 0000-0002-8445-8486Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:differential expression· 2 Research Focus:drug response / drug discovery· 2 Research Focus:protein structure prediction· 2 Assay:proteomics· 2 Approach:statistical model· 2 Research Focus:database / resource· 1 Approach:deep learning· 1 Approach:experimental assay· 1

Frequent Co-Authors

Jonathan Francis-LandauiD· 3 shared Siddharth S. RathiD· 3 shared Burak Berk ÜstündağiD· 2 shared Mehmet SarıkayaiD· 2 shared Oliver Nakano-BakeriD· 2 shared Deniz Tanil YucesoyiD· 1 shared Mehmet Sarikaya· 1 shared Ximing LuiD· 1 shared

Activity by Year

2019-2021 · peak 2/yr

Co-Author Collaboration Network

9 top collaborators · 26 mutual co-author links

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3 shared papersBioinformatics

Jonathan Francis-LandauORCID

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3 papers

Recent·Most cited

Deep Directed Evolution of Solid Binding Peptides for Quantitative Big-Data Generation

Deniz Tanil Yucesoy, Siddharth S. Rath, Jacob Rodriguez, Jonathan Francis-Landau, Oliver Nakano-Baker, Mehmet Sarıkaya

The paper develops a high-throughput peptide-selection protocol to generate a large dataset of solid-binding peptides, emphasizing data quality and enabling future machine learning applications.

bioRxiv · Jan 26, 2021 · PreprintMolecular Biology

A Generalized Similarity Metric for Peptide Binding Affinity Prediction

Jacob Rodriguez, Siddharth S. Rath, Jonathan Francis-Landau, Yekta Demirci, Burak Berk Üstündağ, Mehmet Sarikaya

This paper introduces a generalized similarity metric, the Total Similarity Score, to predict peptide binding affinity by benchmarking it on peptide-protein datasets.

bioRxiv · Aug 19, 2019 · PreprintBioinformatics

VSEPRnet: Physical structure encoding of sequence-based biomolecules for functionality prediction: Case study with peptides

Siddharth S. Rath, Jonathan Francis-Landau, Ximing Lu, Oliver Nakano-Baker, Jacob Rodriguez, Burak Berk Üstündağ, Mehmet Sarıkaya

The paper introduces VSEPRnet, a method to encode biomolecule structures for functionality prediction, demonstrating improved accuracy in predicting peptide-MHC binding affinities.

bioRxiv · May 31, 2019 · PreprintBioinformatics