@article{Childs2019,
title = {Non-parametric analysis of thermal proteome profiles reveals novel drug-binding proteins.},
author = {Childs, Dorothee and Bach, Karsten and Franken, Holger and Anders, Simon and Kurzawa, Nils and Bantscheff, Marcus and Savitski, Mikhail and Huber, Wolfgang},
url = {http://dx.doi.org/10.1074/mcp.TIR119.001481},
year = {2019},
month = {oct},
day = {3},
urldate = {2019-10-29},
journal = {Molecular \& Cellular Proteomics},
doi = {10.1074/mcp.TIR119.001481},
pmid = {31582558},
pmcid = {PMC6885700},
abstract = {Detecting the targets of drugs and other molecules in intact cellular contexts is a major objective in drug discovery and in biology more broadly. Thermal proteome profiling ({TPP}) pursues this aim at proteome-wide scale by inferring target engagement from its effects on temperature-dependent protein denaturation. However, a key challenge of {TPP} is the statistical analysis of the measured melting curves with controlled false discovery rates at high proteome coverage and detection power. We present non-parametric analysis of response curves ({NPARC}), a statistical method for {TPP} based on functional data analysis and nonlinear regression. We evaluate {NPARC} on five independent {TPP} datasets and observe that it is able to detect subtle changes in any region of the melting curves, reliably detects the known targets, and outperforms a melting point-centric, single-parameter fitting approach in terms of specificity and sensitivity. {NPARC} can be combined with established analysis of variance ({ANOVA}) statistics and enables flexible, factorial experimental designs and replication levels. To facilitate access to a wide range of users, a freely available software implementation of {NPARC} is provided. Published under license by The American Society for Biochemistry and Molecular Biology, Inc.}
}




@article{Franken2015,
title = {Thermal proteome profiling for unbiased identification of direct and indirect drug targets using multiplexed quantitative mass spectrometry},
author = {Franken, Holger and Mathieson, Toby and Childs, Dorothee and Sweetman, Gavain M A and Werner, Thilo and T{\"{o}}gel, Ina and Doce, Carola and Gade, Stephan and Bantscheff, Marcus and Drewes, Gerard and Reinhard, Friedrich B M and Huber, Wolfgang and Savitski, Mikhail M},
journal = {Nat. Protoc.},
month = {oct},
number = {10},
pages = {1567--93},
volume = {10},
year = {2015}
}


@article{Reinhard2015,
title = {Thermal proteome profiling monitors ligand interactions with cellular membrane proteins},
author = {Reinhard, Friedrich B M and Eberhard, Dirk and Werner, Thilo and Franken, Holger and Childs, Dorothee and Doce, Carola and Savitski, Maria F{\"{a}}lth and Huber, Wolfgang and Bantscheff, Marcus and Savitski, Mikhail M and Drewes, Gerard},
journal = {Nat. Methods},
month = {dec},
number = {12},
pages = {1129--31},
volume = {12},
year = {2015}
}

@article{Savitski2014,
title = {Tracking cancer drugs in living cells by thermal profiling of the proteome},
author = {Savitski, Mikhail M and Reinhard, Friedrich B M and Franken, Holger and Werner, Thilo and Savitski, Maria F{\"{a}}lth and Eberhard, Dirk and {Martinez Molina}, Daniel and Jafari, Rozbeh and Dovega, Rebecca Bakszt and Klaeger, Susan and Kuster, Bernhard and Nordlund, P{\"{a}}r and Bantscheff, Marcus and Drewes, Gerard},
journal = {Science},
volume = {346},
number = {6205},
pages = {1255784},
year = {2014}
}

@article{Marazzi2002,
title={Bootstrap tests for robust means of asymmetric distributions with unequal shapes},
author={Marazzi, A},
journal={Computational statistics \& data analysis},
volume={39},
number={4},
pages={503--528},
year={2002},
publisher={Elsevier}
}
