| Universal critical dynamics in high resolution neuronal avalanche data N Friedman, S Ito, BAW Brinkman, M Shimono, REL DeVille, KA Dahmen, ... Physical review letters 108 (20), 208102, 2012 | 503 | 2012 |
| Robust ecological pattern formation induced by demographic noise T Butler, N Goldenfeld Physical Review E—Statistical, Nonlinear, and Soft Matter Physics 80 (3 …, 2009 | 167 | 2009 |
| Fluctuation-driven Turing patterns T Butler, N Goldenfeld Physical Review E—Statistical, Nonlinear, and Soft Matter Physics 84 (1 …, 2011 | 137 | 2011 |
| Relative rate and location of intra-host HIV evolution to evade cellular immunity are predictable JP Barton, N Goonetilleke, TC Butler, BD Walker, AJ McMichael, ... Nature communications 7 (1), 11660, 2016 | 108 | 2016 |
| Quorum sensing allows T cells to discriminate between self and nonself TC Butler, M Kardar, AK Chakraborty Proceedings of the National Academy of Sciences 110 (29), 11833-11838, 2013 | 79 | 2013 |
| Evolutionary constraints on visual cortex architecture from the dynamics of hallucinations TC Butler, M Benayoun, E Wallace, W van Drongelen, N Goldenfeld, ... Proceedings of the National Academy of Sciences 109 (2), 606-609, 2012 | 55 | 2012 |
| Extreme genetic code optimality from a molecular dynamics calculation of amino acid polar requirement T Butler, N Goldenfeld, D Mathew, Z Luthey-Schulten Physical Review E—Statistical, Nonlinear, and Soft Matter Physics 79 (6 …, 2009 | 38 | 2009 |
| Identification of drug resistance mutations in HIV from constraints on natural evolution TC Butler, JP Barton, M Kardar, AK Chakraborty Physical Review E 93 (2), 022412, 2016 | 33 | 2016 |
| Predator-prey quasicycles from a path-integral formalism T Butler, D Reynolds Physical Review E—Statistical, Nonlinear, and Soft Matter Physics 79 (3 …, 2009 | 23 | 2009 |
| Efficiently predicting high resolution mass spectra with graph neural networks M Murphy, S Jegelka, E Fraenkel, T Kind, D Healey, T Butler International Conference on Machine Learning, 25549-25562, 2023 | 15 | 2023 |
| Hidden biases in unreliable news detection datasets X Zhou, H Elfardy, C Christodoulopoulos, T Butler, M Bansal arXiv preprint arXiv:2104.10130, 2021 | 13 | 2021 |
| Multi-scale sinusoidal embeddings enable learning on high resolution mass spectrometry data G Voronov, R Lightheart, J Davison, CA Krettler, D Healey, T Butler arXiv preprint arXiv:2207.02980, 2022 | 11 | 2022 |
| MS2Mol: A transformer model for illuminating dark chemical space from mass spectra T Butler, A Frandsen, R Lightheart, B Bargh, J Taylor, TJ Bollerman, ... | 6 | 2023 |
| MS2Prop: A machine learning model that directly predicts chemical properties from mass spectrometry data for novel compounds G Voronov, A Frandsen, B Bargh, D Healey, R Lightheart, T Kind, ... bioRxiv 10 (2022.10), 09.511482, 2022 | 6 | 2022 |
| Optimality properties of a proposed precursor to the genetic code T Butler, N Goldenfeld Physical Review E—Statistical, Nonlinear, and Soft Matter Physics 80 (3 …, 2009 | 2 | 2009 |
| Horizontal Gene Transfer and the Emergence of Darwinian Evolution TC Butler | 1 | 2006 |
| The Renormalization Group as a Method for Analyzing Differential Equations TC Butler | 1 | 2005 |
| MS2Prop: A machine learning model that directly generates de novo predictions of drug-likeness of natural products from unannotated MS/MS spectra G Voronov, R Lightheart, A Frandsen, B Bargh, SE Haynes, E Spencer, ... bioRxiv, 2022.10. 09.511482, 2022 | | 2022 |
| The kinetics and location of intra-host HIV evolution to evade cellular immunity are predictable J Barton, N Goonetilleke, T Butler, B Walker, A McMichael, A Chakraborty APS March Meeting Abstracts 2016, F35. 012, 2016 | | 2016 |
| Data collapse and critical dynamics in neuronal avalanche data T Butler, N Friedman, K Dahmen, J Beggs, L Deville, S Ito APS March Meeting Abstracts 2012, L41. 002, 2012 | | 2012 |
