Project titles for:
Project titles for: 2008-10
- In silico analysis of Larger subunit of AGPase in Rice and Maize
- In silico Analysis of mutated in Larger subunit of AGPase in Maize
- Structural Comparison of Betaine Aldehyde Dehydrogenase-1 of Barley and Rice
- Analysis of Gene Expression Database of Skin Cancer
- Evaluation of Sequence Alignment Tools
- Phylogenetic analysis of Drb 3.2 gene
- Modelling of Smaller subunit of AGPase in Rice and Maize
- Prediction of Protein structure from sequence
- Development of Clinical Information Database of domestic animals
- To identify distant relationship between flavoprotein superfamily
- Promoters comparison in bacteria
- Transport protein features analysis
- Genome deciphering and comparative genomics of Solanaceous genome
- Computational approach in deciphering effect of gene alteration in Arabidopsis Thaliana
- Simulation of conformational changes in protein
As Skin cancer is highly heterogenous and complex cancer type, microarray and gene expression profiling can be used for classification and diagnosis of this cancer. DNA microarrays are tools for assessing the dynamics of genes by gene expression regulation as parallel quantification as a whole that underlie biological and clinical properties of tumors. A publicly available biological database from NCBI was used to highlight candidate genes for skin cancer. Cytoscape 2.6.3 was found as a very useful and user-friendly network analysis software with core providing basic functions that is extensible with an architecture of advanced plugins. Correlation Network Construction and Analysis of microarray skin cancer data file (GDS2200) gives statistical comparison about how gene correlates in skin cancer and also define its various network parameters. Network layout and Statistical Analysis of Network was done to find out the properties of the network. MCODE gene cluster plugin creates 86 gene clusters which can be used to study prognosis of skin cancer. Also, the scoredefined modules were found out. Gene Ontology Analysis was carried out by BiNGO. Qlucore-Omics web browser is a powerful interactive visualization environment and helps to uncover hidden structures and find patterns in large data sets at a faster pace. Differential Gene Expression studies were carried out and 95 dysregulated genes between the two diseased states i.e. Actinic Keratosis and Squamous Cell Carcinoma were identified. DAVID Web Based Bioinformatics tool is highly informative and worldwide acceptable as functional classification clustering tool. Four clusters on the basis of their functional classification were discovered. Statistical parameters used for data analysis were based on Microarray data formats and complex type of cancer. The findings resembled to results of experimental approaches. These type of approaches still requires validation and depends on experimental condition especially on mRNA sampling. We should integrate and relate this data to proteomics and metabolic data for systems level studies of skin cancer and further studies.