Multiclass cancer classification on microarray data has provided the feasibility of cancer diagnosis across all of the common malignancies in parallel. Using multiclass cancer feat...
Data extracted from microarrays are now considered an important source of knowledge about various diseases. Several studies based on microarray data and the use of receiver operat...
Malik Sajjad Ahmed Nadeem, Jean-Daniel Zucker, Bla...
The problem of uncovering transcriptional regulation by transcription factors (TFs) based on microarray data is considered. A novel Bayesian sparse correlated rectified factor mod...
Background: Cluster analysis is a crucial tool in several biological and medical studies dealing with microarray data. Such studies pose challenging statistical problems due to di...
Background: Typical analysis of microarray data ignores the correlation between gene expression values. In this paper we present a model for microarray data which specifically all...
Background: Concomitant with the rise in the popularity of DNA microarrays has been a surge of proposed methods for the analysis of microarray data. Fully controlled "spike-i...
Qianqian Zhu, Jeffrey C. Miecznikowski, Marc S. Ha...
Microarray data usually contains a high level of noisy gene data, the noisy gene data include incorrect, noise and irrelevant genes. Before Microarray data classification takes pla...
The recent development of microarray technology provided unprecedented opportunities to understand the genetic basis of aging. So far, many microarray studies have addressed aging...
Fei Pan, Chi-Hsien Chiu, Sudip Pulapura, Michael R...
The use of DNA microarrays for the analysis of complex biological samples is becoming a mainstream part of biomedical research. One of the most commonly used methods compares the ...
Andrew B. Goryachev, Pascale F. Macgregor, Aled M....
Rapid advances in genome sequencing and gene expression microarray technologies are providing unprecedented opportunities to identify specific genes involved in complex biological...
Indra Neil Sarkar, Paul J. Planet, T. E. Bael, S. ...