Diagnosis of gum cancer cells from DNA/RNA using database mining and support vector regression through high resolution 4D HPCH experiment for sequential assignment of 13C–labeled DNAs/RNAs in gum cancer cells

Abstract

In the current research, diagnosis of gum cancer cells from DNA/RNA using database mining and support vector regression through high resolution 4D HPCH experiment for sequential assignment of 13C–labeled DNAs/RNAs in gum cancer cells are investigated. Diagnosis of gum cancer in biopsy samples relies on morphological analysis using the expertise of histopathologists or cytologists who have many years’ experience in viewing these specimens. This is augmented by techniques which allow gum cancer specific markers to be visualized using diagnosis of gum cancer cells from DNA/RNA using database mining and support vector regression through high resolution 4D HPCH experiment for sequential assignment of 13C–labeled DNAs/RNAs in gum cancer cells, where gene profiles can be visualized using microarray platforms. Characteristic translocations can be detected using fluorescent in situ hybridization (FISH), particularly in haematopathology. The use of optical methods to interrogate gum cancer cells is developing rapidly and diagnosis of gum cancer cells from DNA/RNA using database mining and support vector regression through high resolution 4D HPCH experiment for sequential assignment of 13C–labeled DNAs/RNAs in gum cancer cells provides a new modality, which shows much promise.