Xingdong Feng

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BACKGROUND In the Addona et al. paper (Nature Biotechnology 2009), a large-scale multi-site study was performed to quantify Multiple Reaction Monitoring (MRM) measurements of proteins spiked in human plasma. The unlabeled signature peptides derived from the seven target proteins were measured at nine different concentration levels, and their isotopic(More)
Linear regressions are commonly used to calibrate the signal measurements in proteomic analysis by mass spectrometry. However, with or without a monotone (e.g., log) transformation, data from such functional proteomic experiments are not necessarily linear or even monotone functions of protein (or peptide) concentration except over a very restricted range.(More)
NISS has joined the Clinical Proteomic Technologies for Cancer research initiative that focuses on technologies for cancer biomarker discovery. The overall goal is to foster the building of an integrated foundation of proteomic technologies, data, reagents and reference materials, and analysis systems to systematically advance the application of protein(More)
Randomization is described by Fisher (1935) as the reasoned basis for inference about the effectiveness of treatments. Fisher advocated both using randomization in designing experiments and using " randomization inference " to analyze experiments that have been randomized. Randomization inference is inference that assumes only the physical act of(More)
— Studies of gene expression in primary human disease tissue often span several years in order to achieve reasonably large sample sizes and to collect patient clinical information making this data particularly valuable. Due to the lack of a central repository, this data has only been available through disparate and non-publicly accessible sources following(More)
In this paper we propose a derivative-free optimization algorithm based on conditional moments for finding the maximizer of an objective function. The proposed algorithm does not require calculation or approximation of any order derivative of the objective function. The step size in iteration is determined adaptively according to the local geometrical(More)
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