Publications

* Equal contribution

Journal

    Rapid and accurate prediction of protein homo-oligomer symmetry
    Kshirsagar, Meller, Humphreys, Sledzieski, Xu, Dodhia, Horvitz, Berger, Bowman, Lavista Ferres, Baker, Baek, Nature Communications, 16(2017), 2025.

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    Learning the Language of Antibody Hypervariability
    Singh, Im, Qiu, Macnkess, Gupta, Sorenson, Sledzieski, Erlach, Wendt, Nanfack, Bryson, Berger, Proceedings of the National Academy of Sciences, 122(1):e2418918121, 2024.

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    Democratizing Protein Language Models with Parameter-Efficient Fine-Tuning
    Sledzieski, Kshirsagar, Baek, Berger, Dodhia, Lavista Ferres, Proceedings of the National Academy of Sciences, 121(26):e2405840121, 2024.

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    TT3D: Leveraging Pre-Computed Protein Sequence Models to Predict Protein-Protein Interactions
    Sledzieski*, Devkota*, Singh, Cowen, Berger, Bioinformatics, 39(11):btad663, 2023.

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    Contrastive learning in protein language space predicts interactions between drugs and protein targets
    Singh*, Sledzieski*, Bryson, Cowen, Berger, Proceedings of the National Academy of Sciences, 120(24):e2220778120, 2023.

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    Transfer of knowledge from model organisms to evolutionarily distant non-model organisms: The coral Pocillopora damicornis membrane signaling receptome
    Kumar, Brenner, Sledzieski, Olaosebikan, Lynn-Goin, Putnam, Yang, Lewinski, Singh, Daniels, Cowen, Klein-Seetharaman, Plos one, 18(2):e0270965, 2023.

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    virDTL: Viral recombination analysis through phylogenetic reconciliation and its application to sarbecoviruses and SARS-CoV-2
    Zaman*, Sledzieski*, Wu, Bansal, J Comput Biol, 30(1):3--20, 2023.

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    Topsy-Turvy: integrating a global view into sequence-based PPI prediction
    Singh*, Devkota*, Sledzieski, Berger, Cowen, Bioinformatics, 38(Supplement 1):i264-i272, 2022.

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    D-SCRIPT translates genome to phenome with sequence-based, structure-aware, genome-scale predictions of protein-protein interactions
    Sledzieski*, Singh*, Cowen, Berger, Cell Systems, 12(10):969-982, 2021.

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Conference

    Decoding the Functional Interactome of Non-Model Organisms with PHILHARMONIC
    Sledzieski, Versavel, Singh, Ocitti, Devkota, Kumar, Shhpilker, Roger, Yang, Lewinski, Putnam, Berger, Klein-Seetharaman, Cowen, Conference on Research in Computational Molecular Biology (RECOMB), 2024.

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    BibTeX Citation

    Parameter-Efficient Fine-Tuning of Protein Language Models Improves Prediction of Protein-Protein Interactions
    Sledzieski, Kshirsagar, Baek, Berger, Dodhia, Lavista Ferres, Machine Learning for Structural Biology Workshop at NeurIPS, 2023.

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    Contrasting drugs from decoys
    Sledzieski*, Singh*, Cowen, Berger, Machine Learning for Structural Biology Workshop at NeurIPS, 2022.

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    Adapting Protein Language Models for Rapid Drug-Target Interaction Prediction
    Sledzieski*, Singh*, Cowen, Berger, Machine Learning for Structural Biology Workshop at NeurIPS, 2021.

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    Sequence-based prediction of protein-protein interactions: a structure-aware interpretable deep learning model
    Sledzieski*, Singh*, Cowen, Berger, Conference on Research in Computational Molecular Biology (RECOMB), 2021.

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    TreeFix-TP: Phylogenetic Error Correction for Accurate Reconstruction of Viral Transmission Networks
    Sledzieski*, Zhang, Mandoiu, Bansal, Pacific Symposium on Biocomputing (PSB), 2021.

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Preprint

    Learning the language of protein-protein interactions
    Ullanat, Jing, Sledzieski, Berger, bioRxiv, 2025.

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    Insulin Signaling and Pharmacology in Corals
    Vizgaudis, Kumar, Olaosebikan, Roger, Brenner, Sledzieski, Yang, Lewinski, Singh, Daniels, Cowen, Klein-Seetharaman, Authorea Preprints, 2024.

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    Single-cell mosaicism analysis reveals cell-type-specific somatic mutational burden in Alzheimers Dementia
    Kousi, Boix, Park, Mathys, Sledzieski, Peng, Bennett, Tsai, Kellis, bioRxiv, 2022.

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PhD Thesis: Learning the Language of Biomolecular Interactions (Defense)