Ecobiology of helminth parasites of finfishes and shellfishes of Cochin waters with special reference to Digenetic trematodes

The great number of parasitic species of marine and brackishwater animals that have been described indicates that parasites play an important part in the ecology of the oceans and brackishwaters. Jnspite of their importance, marine and brackish parasites are probably the least known group of organisms. Considering the large number of marine and brackishwater hosts, especially in the tropics, it is no exaggeration to say that the description of marine and brackishwater parasites has hardly begun (Rohde, 1982). With this view in mind, an attempt has been made to study the ecobiology of the helminth parasites of finfishes and shellfishes of eochin waters with special reference to digenetic trematodes. The work is broadly divided into three chapters, Chapter 1 consists of a description of the study area, prevalence of infection and concurrent infections with helminth parasites, seasonal variation, host specificity> and zoogeography of digenetic trematodes; Chapter II deals with the systematics of digenetic trematodes; and Chapter III deals with studies on larval trematodes from molluscs and crustacea, adult from a molluscan host, life-cycle, biology and histopathology

“Reconstruction of Gene Regulatory Network from Expression Profile of Plasma RNA Data of Colorectal Cancer Patients using Soft Computing Techniques”

Microarray data analysis is one of data mining tool which is used to extract meaningful information hidden in biological data. One of the major focuses on microarray data analysis is the reconstruction of gene regulatory network that may be used to provide a broader understanding on the functioning of complex cellular systems. Since cancer is a genetic disease arising from the abnormal gene function, the identification of cancerous genes and the regulatory pathways they control will provide a better platform for understanding the tumor formation and development. The major focus of this thesis is to understand the regulation of genes responsible for the development of cancer, particularly colorectal cancer by analyzing the microarray expression data. In this thesis, four computational algorithms namely fuzzy logic algorithm, modified genetic algorithm, dynamic neural fuzzy network and Takagi Sugeno Kang-type recurrent neural fuzzy network are used to extract cancer specific gene regulatory network from plasma RNA dataset of colorectal cancer patients. Plasma RNA is highly attractive for cancer analysis since it requires a collection of small amount of blood and it can be obtained at any time in repetitive fashion allowing the analysis of disease progression and treatment response.