A Bayesian semi-parametric model for thermal proteome profiling
Fang et al. develop a Bayesian data analysis approach that is better suited to the analysis of Thermal Proteome Profiling (TPP) data than existing data analysis approaches that have limitations with respect to deviations from the expected sigmoid data behaviour. Their approach, which is more compreh...
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| Autores principales: | , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/7779bba951a04cb6ad7afed9774db400 |
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| Sumario: | Fang et al. develop a Bayesian data analysis approach that is better suited to the analysis of Thermal Proteome Profiling (TPP) data than existing data analysis approaches that have limitations with respect to deviations from the expected sigmoid data behaviour. Their approach, which is more comprehensive and sensitive than standard data analysis methods, identified new putative targets and off-targets from published TPP datasets. |
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