Classification of schizophrenia patients with combined analysis of SNP and fMRI data based on sparse representation

Dongdong Lin; Hongbao Cao; Yu Ping Wang; Vince Calhoun

doi:10.1109/BIBM.2011.41

Classification of schizophrenia patients with combined analysis of SNP and fMRI data based on sparse representation

Dongdong Lin, Hongbao Cao, Yu Ping Wang, Vince Calhoun

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Scopus citations

Abstract

We designed a sparse representation clustering (SRC) model to select the significant single nucleotide polymorphisms (SNPs) and proposed a novel SRC with a sliding window model for functional magnetic resonance imaging (fMRI) voxels selection. Then we combined two types of data to classify schizophrenia patients from healthy controls by linear support vector machine (SVM) to achieve a better diagnosis of schizophrenia. The effectiveness of the selected variables (SNPs or voxels) was validated by the leave one out (LOO) cross-validation method. The experimental results show that our proposed SRC method can effectively select the most discriminative variables in both SNPs and fMRI data. In particular, the combination of complementary fMRI and SNP data can significantly improve the classification of schizophrenia patients, which provides new insights in the study of schizophrenia.

Original language	English (US)
Title of host publication	Proceedings - 2011 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2011
Pages	394-397
Number of pages	4
DOIs	https://doi.org/10.1109/BIBM.2011.41
State	Published - Dec 1 2011
Externally published	Yes
Event	2011 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2011 - Atlanta, GA, United States Duration: Nov 12 2011 → Nov 15 2011

Publication series

Name	Proceedings - 2011 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2011

Other

Other	2011 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2011
Country/Territory	United States
City	Atlanta, GA
Period	11/12/11 → 11/15/11

Keywords

Combined analysis
Schizophrenia
Sparse Representation Clustering
Variables selection

ASJC Scopus subject areas

Biomedical Engineering
Health Informatics
Health Information Management

Access to Document

10.1109/BIBM.2011.41

Cite this

Lin, D., Cao, H., Wang, Y. P., & Calhoun, V. (2011). Classification of schizophrenia patients with combined analysis of SNP and fMRI data based on sparse representation. In Proceedings - 2011 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2011 (pp. 394-397). Article 6120472 (Proceedings - 2011 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2011). https://doi.org/10.1109/BIBM.2011.41

Classification of schizophrenia patients with combined analysis of SNP and fMRI data based on sparse representation. / Lin, Dongdong; Cao, Hongbao; Wang, Yu Ping et al.
Proceedings - 2011 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2011. 2011. p. 394-397 6120472 (Proceedings - 2011 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2011).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Lin, D, Cao, H, Wang, YP & Calhoun, V 2011, Classification of schizophrenia patients with combined analysis of SNP and fMRI data based on sparse representation. in Proceedings - 2011 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2011., 6120472, Proceedings - 2011 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2011, pp. 394-397, 2011 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2011, Atlanta, GA, United States, 11/12/11. https://doi.org/10.1109/BIBM.2011.41

Lin D, Cao H, Wang YP, Calhoun V. Classification of schizophrenia patients with combined analysis of SNP and fMRI data based on sparse representation. In Proceedings - 2011 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2011. 2011. p. 394-397. 6120472. (Proceedings - 2011 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2011). doi: 10.1109/BIBM.2011.41

Lin, Dongdong ; Cao, Hongbao ; Wang, Yu Ping et al. / Classification of schizophrenia patients with combined analysis of SNP and fMRI data based on sparse representation. Proceedings - 2011 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2011. 2011. pp. 394-397 (Proceedings - 2011 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2011).

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abstract = "We designed a sparse representation clustering (SRC) model to select the significant single nucleotide polymorphisms (SNPs) and proposed a novel SRC with a sliding window model for functional magnetic resonance imaging (fMRI) voxels selection. Then we combined two types of data to classify schizophrenia patients from healthy controls by linear support vector machine (SVM) to achieve a better diagnosis of schizophrenia. The effectiveness of the selected variables (SNPs or voxels) was validated by the leave one out (LOO) cross-validation method. The experimental results show that our proposed SRC method can effectively select the most discriminative variables in both SNPs and fMRI data. In particular, the combination of complementary fMRI and SNP data can significantly improve the classification of schizophrenia patients, which provides new insights in the study of schizophrenia.",

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Classification of schizophrenia patients with combined analysis of SNP and fMRI data based on sparse representation

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