Literature DB >> 32061181

Machine Learning in Mass Spectrometric Analysis of DIA Data.

Leon Xu1, Adamo Young1, Audrina Zhou1, Hannes Röst1.   

Abstract

Year:  2020        PMID： 32061181     DOI： 10.1002/pmic.201900352

Source DB:  PubMed          Journal:  Proteomics        ISSN： 1615-9853            Impact factor:   3.984


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  5 in total

1.  Accurate Prediction of y Ions in Beam-Type Collision-Induced Dissociation Using Deep Learning.

Authors:  HyeonSeok Shin; Youngmin Park; Kyunggeun Ahn; Sungsoo Kim
Journal:  Anal Chem       Date:  2022-05-24       Impact factor: 8.008

2.  LC-MS peak assignment based on unanimous selection by six machine learning algorithms.

Authors:  Hiroaki Ito; Takashi Matsui; Ryo Konno; Makoto Itakura; Yoshio Kodera
Journal:  Sci Rep       Date:  2021-12-03       Impact factor: 4.379

3.  Deep representation features from DreamDIAXMBD improve the analysis of data-independent acquisition proteomics.

Authors:  Mingxuan Gao; Wenxian Yang; Chenxin Li; Yuqing Chang; Yachen Liu; Qingzu He; Chuan-Qi Zhong; Jianwei Shuai; Rongshan Yu; Jiahuai Han
Journal:  Commun Biol       Date:  2021-10-14

4.  Multichannel CNN Model for Biomedical Entity Reorganization.

Authors:  Ajay Kumar Singh; Ihtiram Raza Khan; Shakir Khan; Kumud Pant; Sandip Debnath; Shahajan Miah
Journal:  Biomed Res Int       Date:  2022-03-19       Impact factor: 3.411

Review 5.  Deep learning neural network tools for proteomics.

Authors:  Jesse G Meyer
Journal:  Cell Rep Methods       Date:  2021-05-17
  5 in total

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