%% Created using Papers on Mon, 05 Sep 2016.
%% http://papersapp.com/papers/

@article{Tautenhahn:2008fx,
author = {Tautenhahn, Ralf and B{\"o}ttcher, Christoph and Neumann, Steffen},
title = {{Highly sensitive feature detection for high resolution LC/MS.}},
journal = {BMC Bioinformatics},
year = {2008},
volume = {9},
number = {1},
pages = {504},
annote = {* The centWave paper.}
}

@article{Smith:2006ic,
author = {Smith, Colin A and Want, Elizabeth J and O'Maille, Grace and Abagyan, Ruben and Siuzdak, Gary},
title = {{XCMS: processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification.}},
journal = {Analytical chemistry},
year = {2006},
volume = {78},
number = {3},
pages = {779--787},
month = feb
}

@article{Prince:2006jj,
author = {Prince, John T and Marcotte, Edward M},
title = {{Chromatographic alignment of ESI-LC-MS proteomics data sets by ordered bijective interpolated warping.}},
journal = {Analytical chemistry},
year = {2006},
volume = {78},
number = {17},
pages = {6140--6152},
month = sep
}

@article{Saghatelian04,
  author = {Saghatelian, A. and Trauger, S. A. and Want, E. J. and Hawkins,
            E. G. and Siuzdak, G. and Cravatt, B. F.},
  title = {Assignment of endogenous substrates to enzymes by global
           metabolite profiling},
  year = {2004},
  journal = {Biochemistry},
  volume = {43},
  pages = {14332--9},
  url = {http://dx.doi.org/10.1021/bi0480335}
}

@article{Danielsson02,
  author = {Danielsson, Rolf and Bylund, Dan and Markides, Karin E.},
  title = {Matched filtering with background suppression for improved
           quality of base peak chromatograms and mass spectra in
           liquid chromatography-mass spectrometry},
  year = {2002},
  journal = {Analytica Chimica Acta},
  volume = {454},
  pages = {167--184},
  url = {http://dx.doi.org/10.1016/S0003-2670(01)01574-4},
}

@article{Smith:2013gr,
author = {Smith, Rob and Ventura, Dan and Prince, John T},
title = {{LC-MS alignment in theory and practice: a comprehensive algorithmic review.}},
journal = {Briefings in bioinformatics},
year = {2013},
volume = {16},
number = {1},
pages = {bbt080--117},
month = nov
}

@article{Ludwig:2018hv,
author = {Ludwig, Christina and Gillet, Ludovic and Rosenberger, George and Amon, Sabine and Collins, Ben C and Aebersold, Ruedi},
title = {{Data-independent acquisition-based SWATH-MS for quantitative proteomics: a tutorial.}},
journal = {Molecular systems biology},
year = {2018},
volume = {14},
number = {8},
pages = {e8126},
month = aug,
affiliation = {Bavarian Center for Biomolecular Mass Spectrometry (BayBioMS), Technical University of Munich (TUM), Freising, Germany tina.ludwig@tum.de.},
doi = {10.15252/msb.20178126},
pmid = {30104418},
pmcid = {PMC6088389},
language = {English},
read = {Yes},
rating = {0},
date-added = {2019-10-03T11:48:47GMT},
date-modified = {2019-10-03T13:31:59GMT},
abstract = {Many research questions in fields such as personalized medicine, drug screens or systems biology depend on obtaining consistent and quantitatively accurate proteomics data from many samples. SWATH-MS is a specific variant of data-independent acquisition (DIA) methods and is emerging as a technology that combines deep proteome coverage capabilities with quantitative consistency and accuracy. In a SWATH-MS measurement, all ionized peptides of a given sample that fall within a specified mass range are fragmented in a systematic and unbiased fashion using rather large precursor isolation windows. To analyse SWATH-MS data, a strategy based on peptide-centric scoring has been established, which typically requires prior knowledge about the chromatographic and mass spectrometric behaviour of peptides of interest in the form of spectral libraries and peptide query parameters. This tutorial provides guidelines on how to set up and plan a SWATH-MS experiment, how to perform the mass spectrometric measurement and how to analyse SWATH-MS data using peptide-centric scoring. Furthermore, concepts on how to improve SWATH-MS data acquisition, potential trade-offs of parameter settings and alternative data analysis strategies are discussed.},
url = {https://onlinelibrary.wiley.com/doi/abs/10.15252/msb.20178126}
}
