AMIA Annu Symp Proc - Automatic selection of preprocessing methods for improving predictions on mass spectrometry protein profiles.

Tópicos

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{ patient(2837) hospit(1953) medic(668) }
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Resumo

Mass spectrometry proteomic profiling has potential to be a useful clinical screening tool. One obstacle is providing a standardized method for preprocessing the noisy raw data. We have developed a system for automatically determining a set of preprocessing methods among several candidates. Our system's automated nature relieves the analyst of the need to be knowledgeable about which methods to use on any given dataset. Each stage of preprocessing is approached with many competing methods. We introduce metrics which are used to balance each method's attempts to correct noise versus preserving valuable discriminative information. We demonstrate the benefit of our preprocessing system on several SELDI and MALDI mass spectrometry datasets. Downstream classification is improved when using our system to preprocess the data.

Resumo Limpo

mass spectrometri proteom profil potenti use clinic screen tool one obstacl provid standard method preprocess noisi raw data develop system automat determin set preprocess method among sever candid system autom natur reliev analyst need knowledg method use given dataset stage preprocess approach mani compet method introduc metric use balanc method attempt correct nois versus preserv valuabl discrimin inform demonstr benefit preprocess system sever seldi maldi mass spectrometri dataset downstream classif improv use system preprocess data

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