article

Predicting Molecular Formulas of Fragment Ions with Isotope Patterns in Tandem Mass Spectra

Authors:

Runsheng ChenAuthors Info & Claims

IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), Volume 2, Issue 3

Pages 217 - 230

https://doi.org/10.1109/TCBB.2005.43

Published: 01 July 2005 Publication History

Abstract

A number of different approaches have been proposed to predict elemental component formulas (or molecular formulas) of molecular ions in low and medium resolution mass spectra. Most of them rely on isotope patterns, enumerate all possible formulas for an ion, and exclude certain formulas violating chemical constraints. However, these methods cannot be well generalized to the component prediction of fragment ions in tandem mass spectra. In this paper, a new method, FFP (Fragment ion Formula Prediction), is presented to predict elemental component formulas of fragment ions. In the FFP method, the prediction of the best formulas is converted into the minimization of the distance between theoretical and observed isotope patterns. And, then, a novel local search model is proposed to generate a set of candidate formulas efficiently. After the search, FFP applies a new multiconstraint filtering to exclude as many invalid and improbable formulas as possible. FFP is experimentally compared with the previous enumeration methods, and shown to outperform them significantly. The results of this paper can help to improve the reliability of de novo in the identification of peptide sequences.

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Cited By

Conrad TLeichtle AHagehülsmann ADiederichs EBaumann SThiery JSchütte C(2006)Beating the noiseProceedings of the Second international conference on Computational Life Sciences10.5555/2111713.2111727(119-128)Online publication date: 27-Sep-2006
https://dl.acm.org/doi/10.5555/2111713.2111727

Index Terms

Predicting Molecular Formulas of Fragment Ions with Isotope Patterns in Tandem Mass Spectra
1. Applied computing
  1. Life and medical sciences
2. Computing methodologies
  1. Machine learning

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cover image IEEE/ACM Transactions on Computational Biology and Bioinformatics

IEEE/ACM Transactions on Computational Biology and Bioinformatics Volume 2, Issue 3

July 2005

95 pages

ISSN:1545-5963

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IEEE Computer Society Press

Washington, DC, United States

Publication History

Published: 01 July 2005

Published in TCBB Volume 2, Issue 3

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Cited By

Conrad TLeichtle AHagehülsmann ADiederichs EBaumann SThiery JSchütte C(2006)Beating the noiseProceedings of the Second international conference on Computational Life Sciences10.5555/2111713.2111727(119-128)Online publication date: 27-Sep-2006
https://dl.acm.org/doi/10.5555/2111713.2111727

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