Sathish Periyasamy

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Genomic abnormalities leading to colorectal cancer (CRC) include somatic events causing copy number aberrations (CNAs) as well as copy neutral manifestations such as loss of heterozygosity (LOH) and uniparental disomy (UPD). We studied the causal effect of these events by analyzing high resolution cytogenetic microarray data of 15 tumor-normal paired(More)
Colorectal cancer (CRC), which has high prevalence in Saudi Arabia and worldwide, needs better understanding by exploiting the latest available cytogenetic microarrays. We used biopsy tissue from consenting colorectal cancer patients to extract DNA and carry out microarray analysis using a CytoScan HD platform from Affymetrix. Patient specific comparisons(More)
Integrated analysis of genomic and transcriptomic level changes holds promise for a better understanding of colorectal cancer (CRC) biology. There is a pertinent need to explain the functional effect of genome level changes by integrating the information at the transcript level. Using high resolution cytogenetics array, we had earlier identified driver(More)
Evolutionary computation (EC) paradigms are inspired by the optimization strategies utilized by biological systems. While these strategies can be found in every level of biological organization, almost all of the EC techniques which comprise techniques from evolutionary algorithm (EA) to swarm intelligence (SI) have been inspired by organism level(More)
In silico representation of cellular systems needs to represent the adaptive dynamics of biological cells, recognizing a cell's multi-objective topology formed by temporally cohesive intracellular structures. The design of these models needs to address the hierarchical and concurrent nature of cellular functions and incorporate the ability to self-organize(More)
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