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Bratton BP, Shaevitz JW, Gitai Z, Morgenstein RM. MreB polymers and curvature localization are enhanced by RodZ and predict E. coli's cylindrical uniformity. Nat Commun. 2018 ;9(1):2797.
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Etzion-Fuchs A, Todd DA, Singh M. dSPRINT: predicting DNA, RNA, ion, peptide and small molecule interaction sites within protein domains. Nucleic Acids Res. 2021 ;49(13):e78.
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Hoshino A, Kim HSang, Bojmar L, Gyan KEnnu, Cioffi M, Hernandez J, et al. Extracellular Vesicle and Particle Biomarkers Define Multiple Human Cancers. Cell. 2020 ;182(4):1044-1061.e18.
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Klibaite U, Berman GJ, Cande J, Stern DL, Shaevitz JW. An unsupervised method for quantifying the behavior of paired animals. Phys Biol. 2017 ;14(1):015006.
Kloosterman AM, Cimermancic P, Elsayed SS, Du C, Hadjithomas M, Donia MS, et al. Expansion of RiPP biosynthetic space through integration of pan-genomics and machine learning uncovers a novel class of lanthipeptides. PLoS Biol. 2020 ;18(12):e3001026.
Koblan LW, Arbab M, Shen MW, Hussmann JA, Anzalone AV, Doman JL, et al. Efficient C•G-to-G•C base editors developed using CRISPRi screens, target-library analysis, and machine learning. Nat Biotechnol. 2021 ;39(11):1414-1425.
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Lee Y-S, Krishnan A, Oughtred R, Rust J, Chang CS, Ryu J, et al. A Computational Framework for Genome-wide Characterization of the Human Disease Landscape. Cell Syst. 2019 ;8(2):152-162.e6.
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Metsky HC, Welch NL, Pillai PP, Haradhvala NJ, Rumker L, Mantena S, et al. Designing sensitive viral diagnostics with machine learning. Nat Biotechnol. 2022 ;40(7):1123-1131.
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Pereira TD, Tabris N, Matsliah A, Turner DM, Li J, Ravindranath S, et al. SLEAP: A deep learning system for multi-animal pose tracking. Nat Methods. 2022 ;19(4):486-495.
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Qin Y, Kernan KF, Fan Z, Park H-J, Kim S, Canna SW, et al. Machine learning derivation of four computable 24-h pediatric sepsis phenotypes to facilitate enrollment in early personalized anti-inflammatory clinical trials. Crit Care. 2022 ;26(1):128.
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Roussarie J-P, Yao V, Rodriguez-Rodriguez P, Oughtred R, Rust J, Plautz Z, et al. Selective Neuronal Vulnerability in Alzheimer's Disease: A Network-Based Analysis. Neuron. 2020 ;107(5):821-835.e12.
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Sealfon RSG, Mariani LH, Kretzler M, Troyanskaya OG. Machine learning, the kidney, and genotype-phenotype analysis. Kidney Int. 2020 ;97(6):1141-1149.
Sohrabi S, Mor DE, Kaletsky R, Keyes W, Murphy CT. High-throughput behavioral screen in C. elegans reveals Parkinson's disease drug candidates. Commun Biol. 2021 ;4(1):203.
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Wang R, Zheng J, Shao X, Ishii Y, Roy A, Bello A, et al. Development of a prognostic composite cytokine signature based on the correlation with nivolumab clearance: translational PK/PD analysis in patients with renal cell carcinoma. J Immunother Cancer. 2019 ;7(1):348.
Wong AK, Sealfon RSG, Theesfeld CL, Troyanskaya OG. Decoding disease: from genomes to networks to phenotypes. Nat Rev Genet. 2021 ;22(12):774-790.
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Zhou J, Schor IE, Yao V, Theesfeld CL, Marco-Ferreres R, Tadych A, et al. Accurate genome-wide predictions of spatio-temporal gene expression during embryonic development. PLoS Genet. 2019 ;15(9):e1008382.