Statistical design for biospecimen cohort size in proteomics-based biomarker discovery and verification studies.

@article{Skates2013StatisticalDF,
  title={Statistical design for biospecimen cohort size in proteomics-based biomarker discovery and verification studies.},
  author={Steven J. Skates and Michael A. Gillette and Joshua LaBaer and Steven A. Carr and Leigh A Anderson and Daniel C. Liebler and David F. Ransohoff and Nader Rifai and Marina V Kondratovich and Živana Te{\vz}ak and Elizabeth Mansfield and Ann L. Oberg and Ian Wright and Grady Barnes and Mitchell T Gail and Mehdi Mesri and Christopher R. Kinsinger and Henry Rodriguez and Emily S. Boja},
  journal={Journal of proteome research},
  year={2013},
  volume={12 12},
  pages={5383-94}
}
Protein biomarkers are needed to deepen our understanding of cancer biology and to improve our ability to diagnose, monitor, and treat cancers. Important analytical and clinical hurdles must be overcome to allow the most promising protein biomarker candidates to advance into clinical validation studies. Although contemporary proteomics technologies support the measurement of large numbers of proteins in individual clinical specimens, sample throughput remains comparatively low. This problem is… CONTINUE READING
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