Pathogenic Viruses and Armamentarium Design covers the latest developments in viral target elucidation and viral control using wet and dry lab strategies. The control and combat strategies and their implementation compiled in this book are a valuable aid in understanding viral disease progression and designing new strategies against existing and evolving viruses. This important resource is a comprehensive compilation of anti-viral approaches designed and devised using computational and other laboratory techniques. The content targets the readership of college students, scientists and research investigators working on the pathogenic virus and development of prophylactics and therapeutics against viral infection. Researchers from biotechnology, infection biology, chemistry and pharmaceutical science will surely benefit from this content. The incorporation of software and tools will also help both experienced and new bioinformaticians and students.

The present book is the outcome of the research work carried out by the main author during Post-graduate studies under the advisement of the Co-author and a little effort to acquaint the agriculture scientists with the method of analyzing data when a number of responses are measured simultaneously for each set of a group of input variables. In the present book, RSM is used to find the optimum doses of nitrogen (N), phosphorus (P) and potassium (K) so that the yield of French Bean (Phaseolus vulgaris L.) is maximum. An appropriate multiresponse model has been fitted for the data related to the growth of French bean (Phaseolus vulgaris L.) and tests of linear dependencies among responses and lack of fit of the multiresponse model have been performed. The four response variables considered for the study are plant height (cm), number of leaves per plant, number of green pods per plant, total yield of green pods (kg/ha). Finally, the optimum operating conditions which optimize the multiresponse objective function have been obtained by converting the problem into Linear Programming Problem (LPP).