Normalization and missing value imputation for label-free LC-MS analysis
نویسندگان
چکیده
منابع مشابه
Is label-free LC-MS/MS ready for biomarker discovery?
Label-free LC-MS methods are attractive for high-throughput quantitative proteomics, as the sample processing is straightforward and can be scaled to a large number of samples. Label-free methods therefore facilitate biomarker discovery in studies involving dozens of clinical samples. However, despite the increased popularity of label-free workflows, there is a hesitance in the research communi...
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PURPOSE The etiology of keratoconus (KC) and the factors governing its progression are not well understood. It has been suggested that this disease might be caused by biochemical alterations in the cornea; changes in the expression profiles of human aqueous humor (hAH) proteins have been observed in some diseases. To gain a new insight into the molecular mechanisms of KC pathology, we examined ...
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The goal of many LC-MS proteomic investigations is to quantify and compare the abundance of proteins in complex biological mixtures. However, the output of an LC-MS experiment is not a list of proteins, but a list of quantified spectral features. To make protein-level conclusions, researchers typically apply ad hoc rules, or take an average of feature abundance to obtain a single protein-level ...
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BACKGROUND Cancers of the urinary bladder are the fifth most commonly diagnosed malignancy in the United States. Early clinical diagnosis of bladder cancer remains a major challenge, and the development of noninvasive methods for detection and surveillance is desirable for both patients and health care providers. APPROACH To identify urinary proteins with potential clinical utility, we enrich...
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ژورنال
عنوان ژورنال: BMC Bioinformatics
سال: 2012
ISSN: 1471-2105
DOI: 10.1186/1471-2105-13-s16-s5