Leveraging sequences missing from the human genome to diagnose cancer
Abstract Background Cancer diagnosis using cell-free DNA (cfDNA) has the potential to improve treatment and survival but has several technical limitations. Methods In this study, we developed a prediction model based on neomers, DNA sequences 13–17 nucleotides in length that are predominantly absent...
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| Main Authors: | Ilias Georgakopoulos-Soares, Ofer Yizhar-Barnea, Ioannis Mouratidis, Candace S. Y. Chan, Michail Patsakis, Akshatha Nayak, Rachael Bradley, Mayank Mahajan, Jasmine Sims, Dianne Laboy Cintron, Ryder Easterlin, Julia S. Kim, Emmalyn Chen, Geovanni Pineda, Guillermo E. Parada, John S. Witte, Christopher A. Maher, Felix Feng, Ioannis Vathiotis, Nikolaos Syrigos, Emmanouil Panagiotou, Andriani Charpidou, Konstantinos Syrigos, Jocelyn Chapman, Mark Kvale, Martin Hemberg, Nadav Ahituv |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-08-01
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| Series: | Communications Medicine |
| Online Access: | https://doi.org/10.1038/s43856-025-01067-3 |
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