High-Accuracy Peptide Mass Fingerprinting Using Peak Intensity Data with Machine Learning
نویسندگان
چکیده
منابع مشابه
Peak bagging for peptide mass fingerprinting
MOTIVATION Mass Spectrometry (MS)-based protein identification via peptide mass fingerprinting (PMF) is a key component in high-throughput proteome research. While PMF was the first commonly used protein identification method, provided higher throughput than the tandem MS-based method, its accuracy is lower than that of the tandem MS method. Thus, it is desirable to develop PMF-based algorithm ...
متن کاملEnhanced peptide mass fingerprinting through high mass accuracy: Exclusion of non-peptide signals based on residual mass.
Peptide mass fingerprinting (PMF) is among the principle methods of contemporary proteomic analysis. While PMF is routinely practiced in many laboratories, the complexity of protein tryptic digests is such that PMF based on unrefined mass spectrometric peak lists is often inconclusive. A number of data processing strategies have thus been designed to improve the quality of PMF peak lists, and t...
متن کاملHigh-Accuracy Peak Picking of Proteomics Data Using Wavelet Techniques
A new peak picking algorithm for the analysis of mass spectrometric (MS) data is presented. It is independent of the underlying machine or ionization method, and is able to resolve highly convoluted and asymmetric signals. The method uses the multiscale nature of spectrometric data by first detecting the mass peaks in the wavelet-transformed signal before a given asymmetric peak function is fit...
متن کاملHigh-accuracy peak picking of proteomics data
A new peak picking algorithm for the analysis of mass spectrometric (MS) data is presented, which is independent of the underlying machine or ionization method and is able to resolve highly convoluted and asymmetric signals. The method uses the multiscale nature of spectrometric data by first detecting the mass peaks in the wavelet-transformed signal. Then, a given asymmetric peak function is f...
متن کاملUsing Peak Intensity and Fragmentation Patterns in Peptide SeQuence IDentification (SQID) - A Bayesian Learning Algorithm for Tandem Mass Spectra
As DNA sequence information becomes increasingly available, researchers are now tackling the great challenge of characterizing and identifying peptides and proteins from complex mixtures. Automatic database searching algorithms have been developed to meet this challenge. This dissertation is aimed at improving these algorithms to achieve more accurate and efficient peptide and protein identific...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Proteome Research
سال: 2008
ISSN: 1535-3893,1535-3907
DOI: 10.1021/pr070088g