Application of Bioinformatics in the Design of Gene Expression Microarrays
Authors: Sabah Khalid, Mohsin Khan, Ping Wang, Xiaohui Liu, Su-Ling Li
Venue: Proceedings of the Second International Symposium on Leveraging Applications of Formal Methods, Verification and Validation (2006)

The declaration that gene expression microarrays serve as invaluable tools for the global characterisation of entire genomes is widely accepted by the scientific community highly involved in microarray technology. Although microarrays have the power to distinguish between the expression levels of genes within cells that are representative of various conditions the immediate results require further mining to determine the genes, which have been differentially expressed. This process narrows down the dataset to only those genes that are of most interest to the researcher from which hypotheses can be generated regarding their significance within the molecular mechanism being investigated. Consequently, this would lead to a more in-depth investigation within the researchers area of expertise and potential further microarray experiments. Such experiments would aim to answer more detailed biological questions arising from the analysis of the initial microarray. As a result of the enhanced focus, it would be ideal to use more specialised microarrays to gain further knowledge into the biological aspect under examination. Although commercially available they may be of limited use if they fail to represent the targeted pathways and biological processes to the extent required. Hence, customised microarrays become extremely advantageous benefiting researchers with particular requirements. Furthermore, due to the immense cost of DNA gene chips it is not feasible to purchase microarrays for every biological question. As a result it becomes imperative for biologists to maximise the use of existing gene sets. In order to achieve this, bioinformatics tools are necessary to extract meaningful data from the gene set according to a biologists requirements. To this end, we have developed the first software called Gene Chip Design which can extract meaningful data from a given gene set according to a biologists needs. Our unique information retrieval software is a powerful, flexible and user-friendly tool aimed at researchers needing to generate personalised custom in-house arrays that represent the genes from specialised biological pathways of interest. With the inbuilt functionality to generate from any given generalised gene set a novel gene chip specific to a researchers interest, our software can be applied within any biological field. We have also integrated an ontology to allow the global functional characterisation of any given gene set, together with the unique ability to categorise genes in a more structured and informative manner within numerous functional groups. Furthermore, our software identifies biological pathways pertaining to genes of interest and more so highlights such genes within complex pathways. These aspects also provide researchers with the control to identify further genes with biological functions of interest to extract from their gene set and incorporate into their unique gene chip. Using our NIA 15K Mouse cDNA Clone Gene Set, we have designed several gene chips including an oncology gene chip. Furthermore, combined with our previous microarray experimental results we have developed a novel immuno-tolerance gene chip that can be used for further studies investigating the molecular mechanisms underlying autoimmune disease. The software and database schema is freely available at ftp://ftp.brunel.ac.uk/cspgssk. Additional material is available online at http://www.brunel.ac.uk/about/acad/health/healthres/researchareas/mi/publications/supplementary. A detailed microarray protocol is available at http://www.ebi.ac.uk/arrayexpress under the Accession Number: E-MEXP-283.