Courses with Gaps

Sampling theory and its critique; subjective probability; likelihood principles; Bayes theorem; Bayesian analysis of Normal theory inference problems; the Behrens-Fisher problem; assessment of model assumptions; robustness of inference; analysis of variance; estimation of variance components; empirical Bayes; some aspects of multivariate problems; sequential nature of Bayesian inference; prior and posterior distributions of parameters in binomial; poisson; exponential and normal populations; comparison of two normal distributions; predictive distributions; decision theory; utility; risk aversion; extensive form of analysis; two-action problems; point estimation; best population problems; economics of sampling

Introduction to microbiology and biochemistry. Classification and growth characteristics of micro-organisms. Enzymes Engineering: including enzyme kinetics, aerobic and anaerobic respirations, metabolic pathways, cell growth kinetics and models

The cell theory. Structures and functions of major cell components. Cell types, constancy and diversity. Cell organelles of prokaryotes and eukaryotes. Chemical composition of cells. Centrifugation and methods of cell fractionation. Structure, function and fractionation of extra- cellular organelles. Water, total body water and its distribution. Regulation of water and electrolyte balance. Disorder of water and electrolyte balance. Acidity and alkalinity, pH and pK values and their effects on cellular activities.

Importance of biogeography; Distribution of species; genera and families: Endemic species and genera; Pan tropical species and genera; Discontinuous species and genera; Factors of distribution (climatic; edaphic; geographic and dispersal effects); Theory of tolerance; Floristic regions of the world; Vegetation mapping

Advanced Regression; Bio-assays; Probit and Logit models; Growth Curves; Logistic Regression; Potency/efficacy determination; Theory of clinical trials; Ethical Issues in Medical Data Collection

Variability in biological data: continuous and discontinuous variables. statistical sampling procedures. observations and problems of estimation. representation and summarisation of biological data. frequency distribution. measures of central tendency and dispersion. Probability theory. normal, binomial and Poisson distribution. t-test, f-test and chi-square test. analysis of variance (ANOVA) and covariance. principles of experimental design. correlation, linear and curvilinear regression and transformation.

Variability in biological data: Continuous and discontinuous variables; statistical sampling procedures – observations and problems of estimation; Representation and summarisation of biological data; Frequency distribution; Measures of central tendency and dispersion; Probability theory; Normal, binomial and Poisson distribution; t-test, F-test and chi-square test, Analysis of variance (ANOVA) and covariance; Principles of experimental design; Correlation, linear and curvilinear regression; Transformation.

Course Contents Definitions. Modelling and design of fermentation systems. Microbial growth kinetics. Design of bio-reactors. Heat and mass transfer. Bioremediation of wastes. design of anaerobic and aerobic systems. Energy from biological systems. Monitoring and control of biological systems. Application of computer to biological processes.

Quality and storage of specific foods; Functional foods; Microbial influence on food production and storage; Quality assurance in the industry; Biotechnology targets in food processing; Improving food quality; Genetically engineered enzymes and additives in foods; Optimization of food processing methods; Microbial biomass and indigenous fermented foods