On peptide de novo sequencing:: a new approach

被引:27
|
作者
Bruni, R
Gianfranceschi, G
Koch, G
机构
[1] PolyDART Data Anal Res Team Polymers, I-03015 Fiuggi, FR, Italy
[2] Univ Roma La Sapienza, Dept Comp Sci & Syst, I-00185 Rome, Italy
[3] Univ Perugia, Dept Cellular & Mol Biol, I-06123 Perugia, Italy
关键词
combinatoilal optimization; de novo sequencing; mass spectrometry; peptide analysis;
D O I
10.1002/psc.595
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
A procedure is presented for the automatic determination of the amino acid sequence of peptides by processing data obtained from mass spectrometry analysis. This is a basic and relevant problem in the field of proteomics. Furthermore, it. has an even higher conceptual and applicative interest in peptide research, as well as in other connected fields. The analysis does not rely on known protein databases, but oil the computation of all amino acid sequences compatible with the given spectral data. By formulating a mathematical model for such combinatorial problems, the structural limitations of known methods are overcome, and efficient solution algorithms can be developed. The results are very encouraging both from the accuracy and computational points of view. Copyright (c) 2004 European Peptide Society and John Wiley & Sons, Ltd.
引用
收藏
页码:225 / 234
页数:10
相关论文
共 50 条
  • [1] An Approach for Peptide Identification by De Novo Sequencing of Mixture Spectra
    Liu, Yi
    Ma, Bin
    Zhang, Kaizhong
    Lajoie, Gilles
    IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, 2017, 14 (02) : 326 - 336
  • [2] ContraNovo: A Contrastive Learning Approach to Enhance De Novo Peptide Sequencing
    Jin, Zhi
    Xu, Sheng
    Zhang, Xiang
    Ling, Tianze
    Dong, Nanqing
    Ouyang, Wanli
    Gao, Zhiqiang
    Chang, Cheng
    Sun, Siqi
    THIRTY-EIGHTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, VOL 38 NO 1, 2024, : 144 - 152
  • [3] Multiplex De Novo Sequencing of Peptide Antibiotics
    Mohimani, Hosein
    Liu, Wei-Ting
    Yang, Yu-Liang
    Gaudencio, Susana P.
    Fenical, William
    Dorrestein, Pieter C.
    Pevzner, Pavel A.
    JOURNAL OF COMPUTATIONAL BIOLOGY, 2011, 18 (11) : 1371 - 1381
  • [4] De novo peptide sequencing by deep learning
    Ngoc Hieu Tran
    Zhang, Xianglilan
    Xin, Lei
    Shan, Baozhen
    Li, Ming
    PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2017, 114 (31) : 8247 - 8252
  • [5] Multiplex De Novo Sequencing of Peptide Antibiotics
    Mohimani, Hosein
    Liu, Wei-Ting
    Yang, Yu-Liang
    Gaudencio, Susana P.
    Fenical, William
    Dorrestein, Pieter C.
    Pevzner, Pavel A.
    RESEARCH IN COMPUTATIONAL MOLECULAR BIOLOGY, 2011, 6577 : 267 - +
  • [6] An efficient algorithm for de novo peptide sequencing
    Brunetti, S
    Dutta, D
    Liberatori, S
    Mori, E
    Varrazzo, D
    ADAPTIVE AND NATURAL COMPUTING ALGORITHMS, 2005, : 312 - 315
  • [7] Metaheuristics based de novo protein sequencing: A new approach
    Boisson, Jean-Charles
    Jourdan, Laetitia
    Talbi, El-Ghazali
    APPLIED SOFT COMPUTING, 2011, 11 (02) : 2271 - 2278
  • [8] An information theoretic approach to rescoring peptides produced by de novo peptide sequencing
    Rose, John R.
    Cleveland, James P.
    Fox, Alvin
    World Academy of Science, Engineering and Technology, 2010, 46 : 200 - 205
  • [9] Antilope-A Lagrangian Relaxation Approach to the de novo Peptide Sequencing Problem
    Andreotti, Sandro
    Klau, Gunnar W.
    Reinert, Knut
    IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, 2012, 9 (02) : 385 - 394
  • [10] UniNovo: a universal tool for de novo peptide sequencing
    Jeong, Kyowon
    Kim, Sangtae
    Pevzner, Pavel A.
    BIOINFORMATICS, 2013, 29 (16) : 1953 - 1962