Proteomic Approaches for Biomarker Discovery in Ulcerative Colitis

Kurokawa, Manae S.; Hatsugai, Moriaki; Noguchi, Yoshiko; Yoshioka, Takuya; Mitsui, Hiroyuki; Yasuda, Hiroshi; Kato, Tomohiro

doi:10.5772/27034

Ulcerative Colitis - Epidemiology, Pathogenesis and Complications 2011

DOI: 10.5772/27034

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Proteomic Approaches for Biomarker Discovery in Ulcerative Colitis

Manae S. Kurokawa¹,

Moriaki Hatsugai²,

Yoshiko Noguchi³

et al.

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2014

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References 42 publications

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Maximum Likelihood Estimation of GEVD: Applications in Bioinformatics

Thomas¹,

Daemen²,

Moor³

2014

IEEE/ACM Trans. Comput. Biol. and Bioinf.

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We propose a method, maximum likelihood estimation of generalized eigenvalue decomposition (MLGEVD) that employs a well known technique relying on the generalization of singular value decomposition (SVD). The main aim of the work is to show the tight equivalence between MLGEVD and generalized ridge regression. This relationship reveals an important mathematical property of GEVD in which the second argument act as prior information in the model. Thus we show that MLGEVD allows the incorporation of external knowledge about the quantities of interest into the estimation problem. We illustrate the importance of prior knowledge in clinical decision making/identifying differentially expressed genes with case studies for which microarray data sets with corresponding clinical/literature information are available. On all of these three case studies, MLGEVD outperformed GEVD on prediction in terms of test area under the ROC curve (test AUC). MLGEVD results in significantly improved diagnosis, prognosis and prediction of therapy response.

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Maximum Likelihood Estimation of GEVD: Applications in Bioinformatics

Thomas¹,

Daemen²,

Moor³

2014

IEEE/ACM Trans. Comput. Biol. and Bioinf.

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show abstract

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Proteomic Approaches for Biomarker Discovery in Ulcerative Colitis

Cited by 1 publication

References 42 publications

Maximum Likelihood Estimation of GEVD: Applications in Bioinformatics

Maximum Likelihood Estimation of GEVD: Applications in Bioinformatics

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