Development of a Fully Automated Image Analysis Method for High Density cDNA and array CGH Microarray Based Genomic Studies

In this thesis, different techniques for image analysis of high density microarrays have been investigated. Most of the existing image analysis techniques require prior knowledge of image specific parameters and direct user intervention for microarray image quantification. The objective of this research work was to develop of a fully automated image analysis method capable of accurately quantifying the intensity information from high density microarrays images. The method should be robust against noise and contaminations that commonly occur in different stages of microarray development.

Fingerprinting of Mangrove Ecosystems along Northern Kerala Coast using Biomarker Approach

Mangrove forests are the most productive and bio-diverse wetlands on earth. It generate a large amount of litter in the form of leaves, branches, twigs, inflorescence and other debris and provides habitat for diverse flora and fauna of marine and terrestrial origin such as bacteria, fungi, algae, lichens, zooplankton, benthos, birds, reptiles and mammals. These systems act as nursery for many fishes and shellfishes. The other sources may also provide important organic carbon inputs; including allochthonous riverine or marine material, autochthonous production by benthic or epiphytic micro- or macroalgae, and local water column production by phytoplankton. Since mangrove sediments are very complex which receives autochthonous and allochthonous organic matter inputs, the information extracted from the analysis of mangrove sediments is the fingerprint of both natural and human-induced changes.