Knowledge guided analysis of microarray data

Knowledge guided analysis of microarray data q

To microarray expression data analysis, it is well accepted that biological knowledge-guided clustering techniques show more advantages than pure mathematical techniques. In this paper, Gene Ontology is introduced to guide the clustering process, and thus a new algorithm capturing both expression pattern similarities and biological function similarities is developed. Our algorithm was validated...

Bisociative Knowledge Discovery for Microarray Data Analysis

The paper presents an approach to computational knowledge discovery through the mechanism of bisociation. Bisociative reasoning is at the heart of creative, accidental discovery (e.g., serendipity), and is focused on finding unexpected links by crossing contexts. Contextualization and linking between highly diverse and distributed data and knowledge sources is therefore crucial for the implemen...

cDNA Microarray Data Normalization

Knowledge Discovery in Microarray Data

We present a method of prioritizing potential drug targets based on their gene expression “signature”. Primary human pre-cursor neuronal cells were treated with three classes (antidepressant, antipsychotic, opiod receptor agonist) of psychoactive drugs for 24 hours. Microarray technology was used to capture expression of ~11, 000 genes induced by these three categories of drugs. It was demonstr...

microarray data analysis for detection and classification of viral infection

dna microarrays consist of collection of dna microscopic spots that in order to form an array attached to a solid surface such as glass, plastic or silicon chip. the pieces of fixed dna considered as a searcher. in this technology it is possible to test sample against thousands probes for specific genes. with this ability, arrays accelerate the biological investigations, gene finding, molecular...