Publications

@article{sledzieski2026landscape,
  title   = {The landscape of machine learning approaches for modeling protein conformational ensembles},
  author  = {Sledzieski and Hanson},
  journal = {Current Opinion in Structural Biology},
  year    = {2026},
  doi     = {10.1016/j.sbi.2026.103253}
}

@inproceedings{catrina2026reverse,
  title     = {Reverse Distillation: Consistently Scaling Protein Language Model Representations},
  author    = {Catrina and Bepler and Sledzieski and Singh},
  booktitle = {International Conference on Learning Representations},
  year      = {2026},
  doi       = {10.48550/arXiv.2603.07710}
}

@article{sledzieski2026planetmd,
  title   = {PLANET-MD: Ultra-fast Proteome-scale Prediction of Allosteric Networks in Proteins},
  author  = {Sledzieski and Hanson},
  journal = {bioRxiv},
  year    = {2026},
  doi     = {10.1101/2025.06.12.659353}
}

@article{golkar2026mimic,
  title   = {MIMIC: A Generative Multimodal Foundation Model for Biomolecules},
  author  = {Golkar and Kovalic and {Espejo Morales} and Sledzieski and Li and Sokolova and Krawezik and Bietti and {Skok Gibbs} and Klypa and Xiong and Lanusse and Parker and Cho and Cranmer and Hehir and McCabe and Meyer and Morel and Mukhopadhyay and Pettee and Qu and Shen and Fouhey and Sotoudeh and Mulligan and Cossio and Hanson and Jones and Troyanskaya and Ho},
  journal = {arXiv},
  year    = {2026},
  doi     = {10.48550/arXiv.2604.24506}
}

@article{ullanat2026learning,
  title   = {Learning the language of protein-protein interactions},
  author  = {Ullanat and Jing and Sledzieski and Berger},
  journal = {Nature Communications},
  year    = {2026},
  volume  = {17},
  number  = {1199},
  doi     = {10.1038/s41467-025-67971-3}
}

@article{kshirsagar2025rapid,
  title   = {Rapid and accurate prediction of protein homo-oligomer symmetry},
  author  = {Kshirsagar and Meller and Humphreys and Sledzieski and Xu and Dodhia and Horvitz and Berger and Bowman and {Lavista Ferres} and Baker and Baek},
  journal = {Nature Communications},
  year    = {2025},
  volume  = {16},
  number  = {2017},
  doi     = {10.1038/s41467-025-57148-3}
}

@inproceedings{sledzieski2025decoding,
  title     = {Decoding the functional interactome of non-model organisms with PHILHARMONIC},
  author    = {Sledzieski and Versavel and Singh and Ocitti and Devkota and Kumar and Shpilker and Roger and Yang and Lewinski and Putnam and Klein-Seetharaman and Berger and Cowen},
  booktitle = {Conference on Research in Computational Molecular Biology (RECOMB)},
  year      = {2025},
  doi       = {10.1101/2024.10.25.620267}
}

@article{singh2024learning,
  title   = {Learning the language of antibody hypervariability},
  author  = {Singh and Im and Qiu and Macnkess and Gupta and Sorenson and Sledzieski and Erlach and Wendt and Nanfack and Bryson and Berger},
  journal = {Proceedings of the National Academy of Sciences},
  year    = {2024},
  volume  = {122},
  number  = {1},
  pages   = {e2418918121},
  doi     = {10.1073/pnas.2418918121}
}

@article{sledzieski2024democratizing,
  title   = {Democratizing protein language models with parameter-efficient fine-tuning},
  author  = {Sledzieski and Kshirsagar and Baek and Berger and Dodhia and {Lavista Ferres}},
  journal = {Proceedings of the National Academy of Sciences},
  year    = {2024},
  volume  = {121},
  number  = {26},
  pages   = {e2405840121},
  doi     = {10.1073/pnas.2405840121}
}

@article{kumar2023transfer,
  title   = {Transfer of knowledge from model organisms to evolutionarily distant non-model organisms: The coral Pocillopora damicornis membrane signaling receptome},
  author  = {Kumar and Brenner and Sledzieski and Olaosebikan and Lynn-Goin and Putnam and Yang and Lewinski and Singh and Daniels and Cowen and Klein-Seetharaman},
  journal = {Plos one},
  year    = {2023},
  volume  = {18},
  number  = {2},
  pages   = {e0270965},
  doi     = {10.1371/journal.pone.0270965}
}

@article{sledzieski2023tt3d,
  title   = {TT3D: Leveraging pre-computed protein sequence models to predict protein-protein interactions},
  author  = {Sledzieski and Devkota and Singh and Cowen and Berger},
  journal = {Bioinformatics},
  year    = {2023},
  volume  = {39},
  number  = {11},
  pages   = {btad663}
}

@article{singh2023contrastive,
  title   = {Contrastive learning in protein language space predicts interactions between drugs and protein targets},
  author  = {Singh and Sledzieski and Bryson and Cowen and Berger},
  journal = {Proceedings of the National Academy of Sciences},
  year    = {2023},
  volume  = {120},
  number  = {24},
  pages   = {e2220778120},
  doi     = {10.1073/pnas.2220778120}
}

@article{singh2022topsyturvy,
  title   = {Topsy-Turvy: integrating a global view into sequence-based PPI prediction},
  author  = {Singh and Devkota and Sledzieski and Berger and Cowen},
  journal = {Bioinformatics},
  year    = {2022},
  volume  = {38},
  number  = {Supplement 1},
  pages   = {i264-i272}
}

@article{kousi2022singlecell,
  title   = {Single-cell mosaicism analysis reveals cell-type-specific somatic mutational burden in Alzheimers Dementia},
  author  = {Kousi and Boix and Park and Mathys and Sledzieski and Peng and Bennett and Tsai and Kellis},
  journal = {bioRxiv},
  year    = {2022},
  doi     = {10.1101/2022.04.21.489103}
}

@inproceedings{sledzieski2022contrasting,
  title     = {Contrasting drugs from decoys},
  author    = {Sledzieski and Singh and Cowen and Berger},
  booktitle = {Machine Learning for Structural Biology Workshop at NeurIPS},
  year      = {2022}
}

@inproceedings{sledzieski2021treefixtp,
  title     = {TreeFix-TP: Phylogenetic error correction for accurate reconstruction of viral transmission networks},
  author    = {Sledzieski and Zhang and Mandoiu and Bansal},
  booktitle = {Pacific Symposium on Biocomputing (PSB)},
  year      = {2021},
  doi       = {10.1142/9789811232701_0012}
}

@inproceedings{sledzieski2021sequencebased,
  title     = {Sequence-based prediction of protein-protein interactions: a structure-aware interpretable deep learning model},
  author    = {Sledzieski and Singh and Cowen and Berger},
  booktitle = {Conference on Research in Computational Molecular Biology (RECOMB)},
  year      = {2021}
}

@article{sledzieski2021dscript,
  title   = {D-SCRIPT translates genome to phenome with sequence-based, structure-aware, genome-scale predictions of protein-protein interactions},
  author  = {Sledzieski and Singh and Cowen and Berger},
  journal = {Cell Systems},
  year    = {2021},
  volume  = {12},
  number  = {10},
  pages   = {969-982}
}

@inproceedings{sledzieski2021adapting,
  title     = {Adapting protein language models for rapid drug-target interaction prediction},
  author    = {Sledzieski and Singh and Cowen and Berger},
  booktitle = {Machine Learning for Structural Biology Workshop at NeurIPS},
  year      = {2021}
}