NDLI: Analysis of Proteomic Mass Spectra Based on Multivariate Feature Fusion Visualization

Content Provider	IEEE Xplore Digital Library
Author	Hui Meng Wenxue Hong Jialin Song Liqiang Wang
Copyright Year	2008
Description	Author affiliation: Coll. of Electr. Eng., Yanshan Univ., Qinhuangdao (Hui Meng; Wenxue Hong; Jialin Song)
Abstract	Protein mass spectrometry (MS) pattern recognition has recently emerged as a new method for cancer diagnosis. Application of proteomic mass spectra coupled with pattern classification techniques to discover novel biomarkers has been successfully used for the predictive diagnoses of several cancer diseases. However, the extraction of good features that can represent the identities of different classes plays the frontal critical factor for effective classification. In addition, another major problem is how to effectively handle a large number of features. This paper address these two frontal issues for MS classification. We propose a method based on graphical multivariate feature fusion and use it to offer a visual representation of high dimensional data. The graphical processing method we propose, relies on using a multilayered structure of feature fusion which produces as output of the lower dimensional representation. We implement feature fusion by combining method of feature selection and feature extraction. The proposed methodology was tested using public MS-based cancer datasets and the results are promising.
Starting Page	672
Ending Page	675
File Size	275971
Page Count	4
File Format	PDF
ISBN	9781424417476
DOI	10.1109/ICBBE.2008.164
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-05-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Proteins Visualization Pattern classification Proteomics Biomarkers Feature extraction Mass spectroscopy Pattern recognition Cancer Diseases
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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