A Data-Mining Scheme for Identifying Peptide Structural Motifs Responsible for Different MS/MS Fragmentation Intensity Patterns.

A Data-Mining Scheme for Identifying Peptide Structural Motifs Responsible for Different MS/MS Fragmentation Intensity Patterns. Research Abstract Details 

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A Data-Mining Scheme for Identifying Peptide Structural Motifs Responsible for Different MS/MS Fragmentation Intensity Patterns. Abstract Text:

Yingying Huang,George C Tseng,Shinsheng Yuan,Ljiljana Pasa-Tolic,Mary S Lipton,Richard D Smith,Vicki H Wysocki,Yingying Huang,George C Tseng,Shinsheng Yuan,Ljiljana Pasa-Tolic,Mary S Lipton,Richard D Smith,Vicki H Wysocki,

Although tandem mass spectrometry (MS/MS) has become an integral part of proteomics, intensity patterns in MS/MS spectra are rarely weighted heavily in most widely used algorithms because they are not yet fully understood. Here a knowledge mining approach is demonstrated to discover fragmentation intensity patterns and elucidate the chemical factors behind such patterns. Fragmentation intensity information from 28 330 ion trap peptide MS/MS spectra of different charge states and sequences went through unsupervised clustering using a penalized K-means algorithm. Without any prior chemistry assumptions, four clusters with distinctive fragmentation patterns were obtained. A decision tree was generated to investigate peptide sequence motif and charge state status that caused these fragmentation patterns. This data-mining scheme is generally applicable for any large data sets. It bypasses the common prior knowledge constraints and reports on the overall peptide fragmentation behavior. It improves the understanding of gas-phase peptide dissociation and provides a foundation for new or improved protein identification algorithms.

A Data-Mining Scheme for Identifying Peptide Structural Motifs Responsible for Different MS/MS Fragmentation Intensity Patterns. Publishing Authors By Initials

Y Huang,GC Tseng,S Yuan,L Pasa-Tolic,MS Lipton,RD Smith,VH Wysocki,Y Huang,GC Tseng,S Yuan,L Pasa-Tolic,MS Lipton,RD Smith,VH Wysocki,

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A Data-Mining Scheme for Identifying Peptide Structural Motifs Responsible for Different MS/MS Fragmentation Intensity Patterns. Journal Published:

PUBLICATION TYPE: Journal Article

Journal: Journal of proteome research

VOLUME: 7

Page Numbers: 70-9

Journal Abbreviation: J. Proteome Res.

ISSN: 1535-3893

DAY: 4

MONTH: 12

YEAR: 2007

A Data-Mining Scheme for Identifying Peptide Structural Motifs Responsible for Different MS/MS Fragmentation Intensity Patterns. Information

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LANGUAGE: eng

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AFFILIATION: vwysocki@email.arizona.edu.

Country: United States

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MEDLINETA: J Proteome Res

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