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ACS Synthetic Biology|October 27, 2023
Coherent Blending of Biophysics-Based Knowledge with Bayesian Neural Networks for Robust Protein Property PredictionHunter Nisonoff, Yixin Wang, Jennifer ListgartenNature Biotechnology|January 18, 2022
Learning protein fitness models from evolutionary and assay-labeled dataChloe Hsu, Hunter Nisonoff, Clara Fannjiang, et al.Nature Communications|September 2, 2021
Epistatic Net allows the sparse spectral regularization of deep neural networks for inferring fitness functionsAmirali Aghazadeh, Hunter Nisonoff, Orhan Ocal, et al.Genome Biology|October 2, 2023
MBE: model-based enrichment estimation and prediction for differential sequencing dataAkosua Busia, Jennifer ListgartenDrug Discovery Today|December 27, 2005
Practical proteomic biomarker discovery: taking a step back to leap forwardJennifer Listgarten, Andrew EmiliMolecular & Cellular Proteomics : MCP|March 3, 2005
Statistical and computational methods for comparative proteomic profiling using liquid chromatography-tandem mass spectrometryJennifer Listgarten, Andrew EmiliJournal of Computational Biology : a Journal of Computational Molecular Cell Biology|January 6, 2017
Flexible Modeling of Genetic Effects on Function-Valued TraitsNicolo Fusi, Jennifer ListgartenCold Spring Harbor Perspectives in Biology|December 5, 2023
Is Novelty Predictable?Clara Fannjiang, Jennifer ListgartenScience (New York, N.Y.)|April 9, 2026
How artificial intelligence is reengineering protein engineeringJennifer Listgarten, Hanlun JiangJournal of Computational Biology : a Journal of Computational Molecular Cell Biology|August 19, 2007
Leveraging information across HLA alleles/supertypes improves epitope predictionDavid Heckerman, Carl Kadie, Jennifer ListgartenPageof 68