Number of features being reduced and the Y-axis represents the average training error in percentage over 100 training times counted in percentage. The training error increases significantly when 23 less relevant features are removed, as indicated by the red arrow. It is then suggested that at most 22 features could be eliminated.<p><b>Copyright information:</b></p><p>Taken from "A machine learning approach to explore the spectra intensity pattern of peptides using tandem mass spectrometry data"</p><p>http://www.biomedcentral.com/1471-2105/9/325</p><p>BMC Bioinformatics 2008;9():325-325.</p><p>Published online 30 Jul 2008</p><p>PMCID:PMC2529326.</p><p></p
Protein identification has been more helpful than before in the diagnosis and treatment of many dise...
Protein identification has been more helpful than before in the diagnosis and treatment of many dise...
ABSTRACT: The identification of proteins from spectra derived from a tandem mass spectrometry experi...
Umber of features being reduced and the Y-axis represents the average training error in percentage o...
N: Red circles: normalized irrelevance scores of the features under non-mobile status. Blue squares:...
by losing HO, NH, etc. Figure 6-B: The comparison of the experimental spectrum (red) versus the spec...
Erimental counterpart. Figure 7-A: The red line represents the sorted scores calculated with the pre...
E input layer representing 35 features. 40 nodes in binary are used to represent the presence of 20 ...
Y losing HO, NH, etc. Figure 5-B: The comparison of the experimental spectrum (red) versus the spect...
Luence on cleavage at its C-terminus is illustrated in the right panel (red dots). The most influent...
Protein identification has been more helpful than before in the diagnosis and treatment of many dise...
A better understanding of the mechanisms involved in gas-phase fragmentation of peptides is essentia...
Abstract Background A better understanding of the mechanisms involved in gas-phase fragmentation of ...
Tandem mass spectrometry (MS/MS) is a powerful tool for identifying peptide sequences. In a typical ...
Motivation: Tandem mass spectrometry provides the means to match mass spectrometry signal observatio...
Protein identification has been more helpful than before in the diagnosis and treatment of many dise...
Protein identification has been more helpful than before in the diagnosis and treatment of many dise...
ABSTRACT: The identification of proteins from spectra derived from a tandem mass spectrometry experi...
Umber of features being reduced and the Y-axis represents the average training error in percentage o...
N: Red circles: normalized irrelevance scores of the features under non-mobile status. Blue squares:...
by losing HO, NH, etc. Figure 6-B: The comparison of the experimental spectrum (red) versus the spec...
Erimental counterpart. Figure 7-A: The red line represents the sorted scores calculated with the pre...
E input layer representing 35 features. 40 nodes in binary are used to represent the presence of 20 ...
Y losing HO, NH, etc. Figure 5-B: The comparison of the experimental spectrum (red) versus the spect...
Luence on cleavage at its C-terminus is illustrated in the right panel (red dots). The most influent...
Protein identification has been more helpful than before in the diagnosis and treatment of many dise...
A better understanding of the mechanisms involved in gas-phase fragmentation of peptides is essentia...
Abstract Background A better understanding of the mechanisms involved in gas-phase fragmentation of ...
Tandem mass spectrometry (MS/MS) is a powerful tool for identifying peptide sequences. In a typical ...
Motivation: Tandem mass spectrometry provides the means to match mass spectrometry signal observatio...
Protein identification has been more helpful than before in the diagnosis and treatment of many dise...
Protein identification has been more helpful than before in the diagnosis and treatment of many dise...
ABSTRACT: The identification of proteins from spectra derived from a tandem mass spectrometry experi...