A mixture model with a reference-based automatic selection of components for disease classification from protein and/or gene expression levels
<p>Abstract</p> <p>Background</p> <p>Bioinformatics data analysis is often using linear mixture model representing samples as additive mixture of components. Properly constrained blind matrix factorization methods extract those components using mixture samples only. How...
Main Authors: | Kopriva Ivica, Filipović Marko |
---|---|
Format: | Article |
Language: | English |
Published: |
BMC
2011-12-01
|
Series: | BMC Bioinformatics |
Online Access: | http://www.biomedcentral.com/1471-2105/12/496 |
Similar Items
-
Applications of Bayesian Gene Selection and Classification with Mixtures of Generalized Singular -Priors
by: Wen-Kuei Chien, et al.
Published: (2013-01-01) -
Reference Gene and Protein Expression Levels in Two Different NAFLD Mouse Models
by: Layanne C. C. Araujo, et al.
Published: (2020-01-01) -
Gene selection and classification in autism gene expression data
by: Al-Jaf, Shilan Sameen Hameed
Published: (2017) -
The impact of reference gene selection in quantification of gene expression levels in guinea pig cervical tissues and cells
by: Lindqvist Annika, et al.
Published: (2013-01-01) -
Gene Expression Data Classification With Kernel Principal Component Analysis
by: Zhenqiu Liu, et al.
Published: (2005-01-01)