Studies on physicochemical and biological properties of protease inhibitor from edible mushroom Pleurotus floridanus

Protease inhibitors are found abundantly in numerous plants, animals and microorganisms, owing their significance to their application in the study of enzyme structures, reaction mechanisms and also their utilization in pharmacology and agriculture. They are (synthetic/natural) substances that act directly on proteases to lower the catalytic rate. Although most of these inhibitory proteins are directed against serine proteases, some target cysteine, aspartyl or metalloproteases (Bode and Huber, 1992). Protease inhibitors are essential for regulating the activity of their corresponding proteases and play key regulatory roles in many biological processes. Applications of protease inhibitors are intimately connected to the proteases they inhibit; an overview of proteases with the modes of regulation of their proteolytic activity is discussed

“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.