Publications by authors named "A K Gnanasekar"

Oncogene amplification is a key driver of cancer pathogenesis. Both breakage fusion bridge (BFB) cycles and extrachromosomal DNA (ecDNA) can lead to high oncogene copy numbers, but the impact of BFB amplifications on intratumoral heterogeneity, treatment response, and patient survival remains poorly understood due to detection challenges with DNA sequencing. We introduce an algorithm, OM2BFB, designed to detect and reconstruct BFB amplifications using optical genome mapping (OGM).

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The chromosomal theory of inheritance dictates that genes on the same chromosome segregate together while genes on different chromosomes assort independently. Extrachromosomal DNAs (ecDNAs) are common in cancer and drive oncogene amplification, dysregulated gene expression and intratumoural heterogeneity through random segregation during cell division. Distinct ecDNA sequences, termed ecDNA species, can co-exist to facilitate intermolecular cooperation in cancer cells.

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Conducting cells of the heart and nerve cells of the brain are having the ability to generate and transmit electrical signals. Recording of neural signals became an important research issue for better analysis and better control of neurological functions by using implantable devices. In neural recording systems, the most critical part is the power constraint neural amplifier.

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Glaucoma is a major threatening cause, in which it affects the optical nerve to lead to a permanent blindness to individuals. The major causes of Glaucoma are high pressure to eyes, family history, irregular sleeping habits, and so on. These kinds of causes lead to Glaucoma easily, and the effect of such disease leads to heavy damage to the internal optic nervous system and the affected person will get permanent blindness within few months.

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Background: The mechanisms of carcinogenesis from viral infections are extraordinarily complex and not well understood. Traditional methods of analyzing RNA-sequencing data may not be sufficient for unraveling complicated interactions between viruses and host cells. Using RNA and DNA-sequencing data from The Cancer Genome Atlas (TCGA), we aim to explore whether virus-induced tumors exhibit similar immune-associated (IA) dysregulations using a new algorithm we developed that focuses on the most important biological mechanisms involved in virus-induced cancers.

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