Feature Selection for Classification of SELDI-TOF-MS Proteomic Profiles-Reference-Cited by-同舟云学术

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Feature Selection for Classification of SELDI-TOF-MS Proteomic Profiles

Published:2005 Issue:4 Volume:4 Page:227-246
ISSN:1175-5636
Container-title:Applied Bioinformatics
language:en
Short-container-title:Applied Bioinformatics

Author:

Hauskrecht Milos,Pelikan Richard,Malehorn David E,Bigbee William L,Lotze Michael T,Zeh Herbert J,Whitcomb David C,Lyons-Weiler James

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,General Agricultural and Biological Sciences,Information Systems

Reference36 articles.

1. Use of proteomic patterns in serum to identify ovarian cancer

2. Proteomic approaches to biomarker discovery in prostate and bladder cancers

3. Detection of cancer-specific markers amid massive mass spectral data

4. Proteomic analysis and identification of new biomarkers and therapeutic targets for invasive ovarian cancer

5. Proteomics and Bioinformatics Approaches for Identification of Serum Biomarkers to Detect Breast Cancer

Cited by 22 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Change-point detection method for clinical decision support system rule monitoring;Artificial Intelligence in Medicine;2018-09

2. Investigating Key Genes in Type 2 Diabetes Mellitus via Combining mAP-KL and Mutual Information Network;Current Bioinformatics;2017-09-26

3. Biomarkers for pancreatic cancer: Recent achievements in proteomics and genomics through classical and multivariate statistical methods;World Journal of Gastroenterology;2014

4. Proteomics-Based Theranostics;Cancer Theranostics;2014

5. Combining multiple hypothesis testing and affinity propagation clustering leads to accurate, robust and sample size independent classification on gene expression data;BMC Bioinformatics;2012-10-17

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