Association Analysis Techniques for Discovering Functional Modules from Microarray Data [PDF]
AbstractAn application of great interest in microarray data analysis is the identification of a group of genes that show very similar patterns of expression in a data set, and are expected to represent groups of genes that perform common/similar functions, also known as functional modules.
Gaurav Pandey +3 more
core +3 more sources
EMMA 2 – A MAGE-compliant system for the collaborative analysis and integration of microarray data [PDF]
Background Understanding transcriptional regulation by genome-wide microarray studies can contribute to unravel complex relationships between genes.
Mertens Dominik +16 more
doaj +2 more sources
Microarray Technique, Analysis, and Applications in Dermatology [PDF]
The Human Genome Project, completed in 2003, identified the sequence of the approximately 25,000 genes that comprise the human genome. Knowledge of the structure of the human genome opened the doors to studying the actual function of specific genes, which is necessary to understanding health and disease.
Villaseñor-Park, Jennifer +1 more
openaire +2 more sources
Microarray image processing: A novel neural network framework [PDF]
This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Due to the vast success of bioengineering techniques, a series of large-scale analysis tools has been developed to discover the functional organization of ...
Zineddin, Bachar
core +6 more sources
Adaptive techniques for microarray image analysis with related quality assessment [PDF]
We propose novel techniques for microarray image analysis. In particular, we describe an overall pipeline able to solve the most common problems of microarray image analysis. We pro- pose the microarray image rotation algorithm (MIRA) and the statis- tical gridding pipeline (SGRIP) as two advanced modules devoted to restoring the original microarray ...
Sebastiano Battiato +4 more
openaire +3 more sources
Visualization-based cancer microarray data classification analysis [PDF]
MOTIVATION: Methods for analyzing cancer microarray data often face two distinct challenges: the models they infer need to perform well when classifying new tissue samples while at the same time providing an insight into the patterns and gene ...
Minca Mramor +7 more
core +2 more sources
Copasetic analysis: a framework for the blind analysis of microarray imagery [PDF]
The official published version can be found at the link below.From its conception, bioinformatics has been a multidisciplinary field which blends domain expert knowledge with new and existing processing techniques, all of which are focused on a common ...
Liu, X, Wang, Z, Fraser, K, O'Neill, P
core +1 more source
Information visualization for DNA microarray data analysis: A critical review [PDF]
Graphical representation may provide effective means of making sense of the complexity and sheer volume of data produced by DNA microarray experiments that monitor the expression patterns of thousands of genes simultaneously.
Kuljis, J +5 more
core +1 more source
Ensemble machine learning on gene expression data for cancer classification [PDF]
Whole genome RNA expression studies permit systematic approaches to understanding the correlation between gene expression profiles to disease states or different developmental stages of a cell.
Tan, A C, Gilbert, D
core +4 more sources
Identification of humoral immune responses in protein microarrays using DNA microarray data analysis techniques [PDF]
Abstract Motivation: We present a study of antigen expression signals from a newly developed high-throughput protein microarray technique. These signals are a measure of antibody–antigen binding activity and provide a basis for understanding humoral immune responses to various infectious agents and supporting vaccine and diagnostic ...
Suman Sundaresh +7 more
openaire +6 more sources

