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Competition-based FDR control has been commonly used for over a decade in the computational mass spectrometry community (Elias and Gygi, 2007).
An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database
J. K. Eng, A. L. McCormack, and J. R. Yates, III · 1994
Earlier work this paper cites.
Controlling the false discovery rate: a practical and powerful approach to multiple testing
Y. Benjamini and Y. Hochberg · 1995
Earlier work this paper cites.
On the adaptive control of the false discovery rate in multiple testing with independent statistics
Y. Benjamini and Y. Hochberg · 2000
Earlier work this paper cites.
Significance analysis of microarrays applied to the ionizing radiation response
V. G. Tusher, R. Tibshirani, and G. Chu · 2001
Earlier work this paper cites.
A direct approach to false discovery rates
J. D. Storey · 2002
Earlier work this paper cites.
Statistical significance for genome-wide studies
J. D. Storey and R. Tibshirani · 2003
Earlier work this paper cites.
Transcriptional regulatory code of a eukaryotic genome
C. T. Harbison, D. B. Gordon, T. I. Lee, N. Rinaldi, K. D. Macisaac, T. D. Danford, N. M. Hannett, J. Tagne, D. B. Reynolds, J. Yoo, E.G. Jennings, J. Zeitlinger, D.K. Pokholok, M. Kellis, P. A. Rolfe, K. T. Takusagawa, E. S. Lander, D. K. Gifford, E. Fraenkel, and R. A. Young · 2004
Earlier work this paper cites.
Strong control, conservative point estimation, and simultaneous conservative consistency of false discovery rates: A unified approach
J. D. Storey, J. E. Taylor, and D. Siegmund · 2004
Earlier work this paper cites.
Adaptive linear step-up procedures that control the false discovery rate
Y. Benjamini, A. M. Krieger, and D. Yekutieli · 2006
Earlier work this paper cites.
Automated protein identification by tandem mass spectrometry: Issues and strategies
M. Muller P. Hernandez and R. D. Appel · 2006
Earlier work this paper cites.
Target-decoy search strategy for increased confidence in large-scale protein identifications by mass spectrometry
J. E. Elias and S. P. Gygi · 2007
Earlier work this paper cites.
The standard protein mix database: a diverse data set to assist in the production of improved peptide and protein identification software tools
J. Klimek, J. S. Eddes, L. Hohmann, J. Jackson, A. Peterson, S. Letarte, P. R. Gafken, J. E. Katz, P. Mallick, H. Lee, A. Schmidt, R. Ossola, J. K. Eng, R. Aebersold, and D. B. Martin · 2008
Earlier work this paper cites.
Gimsan: a gibbs motif finder with significance analysis
P. Ng and U. Keich · 2008
Earlier work this paper cites.
Rapid and accurate peptide identification from tandem mass spectra
C. Y. Park, A. A. Klammer, L. Käll, M. P. MacCoss, and W. S. Noble · 2008
Earlier work this paper cites.
MUDE: a new approach for optimizing sensitivity in the target-decoy search strategy for large-scale peptide/protein identification
F. R. Cerqueira, A. Graber, B. Schwikowski, and C. Baumgartner · 2010
Earlier work this paper cites.
Target-decoy search strategy for mass spectrometry-based proteomics
J. E. Elias and S. P. Gygi · 2010
Earlier work this paper cites.
A survey of computational methods and error rate estimation procedures for peptide and protein identification in shotgun proteomics
A. I. Nesvizhskii · 2010
Cited alongside, same era.
Faster SEQUEST searching for peptide identification from tandem mass spectra
B. Diament and W. S. Noble · 2011
Cited alongside, same era.
False discovery rates in spectral identification
K. Jeong, S. Kim, and N. Bandeira · 2012
Cited alongside, same era.
Computational and statistical analysis of protein mass spectrometry data
W. S. Noble and M. J. MacCoss · 2012
Cited alongside, same era.
Determining the calibration of confidence estimation procedures for unique peptides in shotgun proteomics
V. Granholm, J. F. Navarro, W. S. Noble, and L. Käll · 2013
Cited alongside, same era.
PANTHER in 2013: modeling the evolution of gene function, and other gene attributes, in the context of phylogenetic trees
Unbiased false discovery rate estimation for shotgun proteomics based on the target-decoy approach
L. I. Levitsky, M V. Ivanov, A. A. Lobas, and M. V. Gorshkov · 2017
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Param-Medic: A tool for improving MS/MS database search yield by optimizing parameter settings
D. H. May, K. Tamura, and W. S. Noble · 2017
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Diversity of amyloid-beta proteoforms in the Alzheimer’s disease brain
N. C. Wildburger, T. J. Esparza, R. D. LeDuc, R. T. Fellers, P. M. Thomas, N. J. Cairns, N. L. Kelleher, R. J. Bateman, and D. L. Brody · 2017
Later among the works it cites.
NeuralFDR: Learning discovery thresholds from hypothesis features
F. Xia, M. J. Zhang, J. Y. Zou, and D. Tse · 2017
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Mapping the ecological networks of microbial communities
Y. Xiao, M. T. Angulo, J. Friedman, M. K. Waldor, S. T. WeissT, and Y.-Y. Liu · 2017
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H. Mi, A. Muruganujan, and P. T. Thomas · 2013
Cited alongside, same era.
Controlling the false discovery rate via knockoffs
R. F. Barber and Emmanuel J. Candès · 2015
Cited alongside, same era.
K. He, Y. Fu, W.-F. Zeng, L. Luo, H. Chi, C. Liu, L.-Y. Qing, R.-X. Sun, and S.-M. He · 2015
Cited alongside, same era.
On the importance of well calibrated scores for identifying shotgun proteomics spectra
U. Keich and W. S. Noble · 2015
Cited alongside, same era.
Improved false discovery rate estimation procedure for shotgun proteomics
U. Keich, A. Kertesz-Farkas, and W. S. Noble · 2015
Cited alongside, same era.
Tau post-translational modifications in wild-type and human amyloid precursor protein transgenic mice
M. Morris, G. M. Knudsen, S. Maeda, J. C. Trinidad, A. Ioanoviciu, A. L. Burlingame, and L. Mucke · 2015
Cited alongside, same era.
A scalable approach for protein false discovery rate estimation in large proteomic data sets
M. M. Savitski, M. Wilhelm, H. Hahne, B. Kuster, and M. Bantscheff · 2015
Cited alongside, same era.
Yingying Fan, Jinchi Lv, Mahrad Sharifvaghefi, and Yoshimasa Uematsu · 2018
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Model-based and model-free machine learning techniques for diagnostic prediction and classification of clinical outcomes in parkinson’s disease
Chao Gao, Hanbo Sun, Tuo Wang, Ming Tang, Nicolaas I Bohnen, Martijn LTM Müller, Talia Herman, Nir Giladi, Alexandr Kalinin, Cathie Spino, et al · 2018
Later among the works it cites.
A direct approach to false discovery rates by decoy permutations
K. He, M. Li, Y. Fu, F. Gong, and X. Sun · 2018
Later among the works it cites.
Averaging strategy to reduce variability in target-decoy estimates of false discovery rate
U. Keich, K. Tamura, and W. S. Noble · 2018
Later among the works it cites.
DeepPINK: reproducible feature selection in deep neural networks
Y. Y. Lu, Y. Fan, J. Lv, and W. S. Noble · 2018
Later among the works it cites.
Global quantitative analysis of the human brain proteome in Alzheimer’s and Parkinson’s disease
L. Ping, D. M. Duong, L. Yin, M. Gearing, J. J. Lah, A. I. Levey, and N. T. Seyfried · 2018
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Multiple competition based fdr control
K. Emery, S. Hasam, W. S. Noble, and U. Keich · 2019
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Proteomics and the microbiome: pitfalls and potential
H. Lin, Q. Y. He, L. Shi, M. Sleeman, M. S. Baker, and E. C. Nice · 2019
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Predicting gene expression in the human malaria parasite
D. F. Read, K. Cook, Y. Y. Lu, K. Le Roch, and W. S. Noble · 2019
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Progress and challenges in ocean metaproteomics and proposed best practices for data sharing
M. A. Saito, E. M. Bertrand, M. E. Duffy, D. A. Gaylord, N. A. Held, W. J. Hervey, R. L. Hettich, P. D. Jagtap, M. G. Janech, D. B. Kinkade, D. H. Leary, M. R. McIlvin, E. K. Moore, R. M. Morris, B. A. Neely, B. L. Nunn, J. K. Saunders, A. I. Shepherd, N. I. Symmonds, and D. A. Walsh · 2019
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qvalue: Q-value estimation for false discovery rate control , 2019
John D. Storey, Andrew J. Bass, Alan Dabney, and David Robinson · 2019
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