The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Predicting evolution from the shape of genealogical trees
Open accessAbstract
Given a sample of genome sequences from an asexual population, can one predict its evolutionary future? Here we demonstrate that the branching patterns of reconstructed genealogical trees contains information about the relative fitness of the sampled sequences and that this information can be used to predict successful strains. Our approach is based on the assumption that evolution proceeds by accumulation of small effect mutations, does not require species specific input and can be applied to any asexual population under persistent selection pressure. We demonstrate its performance using historical data on seasonal influenza A/H3N2 virus. We predict the progenitor lineage of the upcoming influenza season with near optimal performance in 30% of cases and make informative predictions in 16 out of 19 years. Beyond providing a tool for prediction, our ability to make informative predictions implies persistent fitness variation among circulating influenza A/H3N2 viruses.
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Python for scientific computing
Oliphant, T. E. (2007) · Computing in Science & Engineering · doi:10.1109/mcse.2007.58 · Cited by 3,303 · cited 3×
“stats (Oliphant, 2007).”
MethodMapping the Antigenic and Genetic Evolution of Influenza Virus
Smith, D. J., Lapedes, A. S., de Jong, J. C., Bestebroer, T. M., Rimmelzwaan, G. F., Osterhaus, A. D. M. E., & Fouchier, R. A. M. (2004) · Science · doi:10.1126/science.1097211 · Cited by 1,868
Cited by
Eleven grand challenges in single-cell data science
Lähnemann, D., Köster, J., Szczurek, E., McCarthy, D. J., Hicks, S. C., Robinson, M. D., Vallejos, C. A., Campbell, K. R., Beerenwinkel, N., Mahfouz, A., et al. (2020) · Genome Biology · doi:10.1186/s13059-020-1926-6 · Cited by 1,327
Mutation effects predicted from sequence co-variation
Hopf, T. A., Ingraham, J. B., Poelwijk, F. J., Schärfe, C. P. I., Springer, M., Sander, C., & Marks, D. S. (2017) · Nature Biotechnology · doi:10.1038/nbt.3769 · Cited by 775
Deciphering cell states and genealogies of human haematopoiesis
Weng, C., Yu, F., Yang, D., Poeschla, M., Liggett, L. A., Jones, M. G., Qiu, X., Wahlster, L., Caulier, A., Hussmann, J. A., et al. (2024) · Nature · doi:10.1038/s41586-024-07066-z · Cited by 171
Ferreiro, D., González-Vázquez, L. D., Prado-Comesaña, A., & Arenas, M. (2025) · eLife · doi:10.7554/elife.106365.3 · Cited by 3
Metadata
- Authors
- Neher, R. A., Russell, C. A., & Shraiman, B. I.
- Venue
- eLife
- Publisher
- eLife Sciences Publications, Ltd
- Published
- 2014-11-11
- Volume
- 3
- ISSN
- 2050-084X (ISSN-L)
- OpenAlex
- W2134246371
- Cited by
- 216
- References
- 2
- FWCI
- 10.10
- Type
- journal article
- Language
- en
- Open access
- gold
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