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Samuel Payne

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As seen in: Nature, ACS Publications, BioRxiv, Cell Press
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Articles

Better Inputs, Better Learning: A Peptide Embedding Tutorial for Proteomic Mass Spectrometry

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By Luke Squires, Alfred Nilsson, Lukas Käll, Samuel Payne
| dx.doi.org
Journal of Proteome Research Cite this: J. Proteome Res. 2026, XXXX, XXX Click to copy citationCitation copied! . This publication is licensed under CC-BY 4.0 . You are free to share (copy and redistribute) this article in any medium or format and to adapt (remix, transform, and build upon) the material for any purpose, even commercially within the parameters below: Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator.
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Integrated Proteogenomic Characterization of Human High-Grade Serous Ovarian Cancer

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By Tao Liu, Zhen Zhang, Samuel Payne, Bai Zhang, Jason McDermott, Jian-Ying Zhou, Vladislav A. Petyuk, Li Chen, Shisheng Sun, Feng Yang, Lijun Chen, Jing Wang, Punit Shah, Yuan Tian, Marina A. Gritsenko, Matthew Monroe, Stefani N. Thomas, Song Nie, Chaochao Wu, Ronald Moore, Kun-Hsing Yu, David Tabb, David Fenyö, Vineet Bafna, Yue Wang, Henry Rodriguez, Emily Boja, Robert Rivers, Lori J. Sokoll, Heng Zhu, Ie-Ming Shih, Leslie Cope, Akhilesh Pandey, Bing Zhang, Michael Snyder, Douglas A. Levine, Richard Smith, Daniel Chan, Karin D. Rodland, Debjit Ray, Paul Aiyetan, Sunghee Woo, Therese R. Clauss, Caitlin Choi, Tara Hiltke
| Cell Press Verified
Main text (Cell 166, 755–765; July 28, 2016) Our paper characterized proteomics and phosphoproteomics data from high-grade serous ovarian cancer tumors. As part of this analysis, we, the authors, used machine learning to identify a set of protein signatures that were predictive of patient survival after treatment.
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Evaluating a large language model’s ability to solve programming exercises from an introductory bioinformatics course

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By Stephen R. Piccolo, Paul Denny, Andrew Luxton-Reilly, Samuel Payne
| scholarsarchive.byu.edu
computer code, computer programming, artificial intelligence tools, bioinformatics Piccolo SR, Denny P, Luxton-Reilly A, Payne SH, Ridge PG (2023) Evaluating a large language model’s ability to solve programming exercises from an introductory bioinformatics course. PLoS Comput Biol 19(9): e1011511.
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