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This is a course on standard data structures, including sorting and searching and using the Java language. The topics include: stages of software development; testing; UML diagrams; elementary data structures (lists, stacks, queues, and maps); use of elementary data structures in application frameworks (e.g., JFC); searching; sorting; and introduction to asymptotic complexity analysis.

Introduction to the study of molecular basis of inheritance. Starts with classical Mendelian genetics and proceeds to the study and function of DNA, gene expression and regulation in prokaryotes and eukaryotes, genome dynamics and the role of genes in development, and cancer. All topics include discussions of current research advances. Accompanied by laboratory section that explores the lecture topics in standard wet laboratory experiments and in computer simulations.

Chemical kinetics, solution theories with applications to separation processes, electrolytes, polyelectrolytes, regular solutions and phase equilibria, and laboratory practice in the measurements of physical properties and rate processes.

Experimental approach to spectroscopy. Topics include Fourier Transform infrared spectroscopy, ultraviolet, visible and fluorescence measurements, atomic absorption spectroscopy, and nuclear magnetic resonance spectroscopy.

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Simple harmonic motion, oscillations and pendulums; Fourier analysis; wave properties; wave-particle dualism; the Schrödinger equation and its interpretation; wave functions; the Heisenberg uncertainty principle; quantum mechanical tunneling and application; quantum mechanics of a particle in a "box," the hydrogen atom; electronic spin; properties of many electron atoms; atomic spectra; principles of lasers and applications; electrons in solids; conductors and semiconductors; the n-p junction and the transistor; properties of atomic nuclei; radioactivity; fusion and fission. Spring Semester.

Introduces the essentials of probability theory and elementary statistics. Lectures and assignments greatly stress the manifold applications of probability and statistics to computer science, production management, quality control, and reliability. A statistical computer package is used throughout the course for teaching and for assignments. Contents include: descriptive statistics, pictorial and tabular methods, and measures of location and of variability; sample space and events, probability axioms, and counting techniques; conditional probability and independence, and Bayes' formula; discrete random variables, distribution functions and moments, and binomial and Poisson distributions; continuous random variables, densities and moments, normal, gamma, and exponential and Weibull distributions unions; distribution of the sum and average of random samples; the Central Limit Theorem; confidence intervals for the mean and the variance; hypothesis testing and p-values, and applications for the mean; simple linear regression, and estimation of and inference about the parameters; and correlation and prediction in a regression model.

Theory and practice of analytical chemistry. Topics include sampling techniques, potentiometric and conductometric titrations, chromatographic separations (gas and high-performance liquid chromatography), polarimetry, and gas chromatography-mass spectrometry.

Discussions include metabolic pathways in biosynthesis and catabolism of biomolecules, including carbohydrates, proteins, lipids, and nucleic acids. The hormonal regulation of metabolism, as well as vitamin metabolism, is presented.

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The behavior of and interactions between individual participants in the economic system are covered. In addition to providing a theoretical basis for the analysis of these economic questions, the course also develops applications of these theories to a number of current problems. Topics include: the nature of economic decisions, the theory of market processes, models of imperfect competition, public policy towards competition, and the allocation of factors of production.

This course provides the background necessary for advanced study of mathematics or computer science. Topics include propositional calculus, predicates and quantifiers, elementary set theory, countability, functions, relations, proof by induction, elementary combinatorics, elements of graph theory, mends, and elements of complexity theory.

This is a course on more complex data structures, and algorithm design and analysis, using the C language. Topics include: advanced and/or balanced search trees; hashing; further asymptotic complexity analysis; standard algorithm design techniques; graph algorithms; complex sort algorithms; and other "classic" algorithms that serve as examples of design techniques.

Fundamentals of control processes governing physiological systems analyzed at the cellular and molecular level. Biological signal transduction and negative feedback control of metabolic processes. Examples from sensory, nervous, cardiovascular, and endocrine systems. Deviations that give rise to abnormal states; their detection, and the theory behind the imaging and diagnostic techniques such as MRI, PET, SPECT; and the design and development of therapeutic drugs. The principles, uses, and applications of biomaterials and tissue engineering techniques; and problems associated with biocompatibility. Students (or groups of students) are expected to write and present a term project.

Discusses the physical and structural chemistry of proteins and nucleotides, as well as the functional role these molecules play in biochemistry. Extensive use of known X-ray structural information will be used to visualize the three-dimensional structure of these biomolecules. This structural information will be used to relate the molecules to known functional information.

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Introduction to the design of relational databases and the use of standard relational query languages. Topics include: relational schemas; keys and foreign key references; relational algebra (as an introduction to SQL); SQL; Entity-Relationship (ER) database design; translating from ER models to relational schemas and from relational schemas to ER models; functional dependencies; and normalization.

The relationship of the chemical and physical structure of biological macromolecules to their biological functions as derived from osmotic pressure, viscosity, light and X-ray scatting, diffusion, ultracentrifugation, and electrophoresis. The course is subdivided into: 1) properties, functions, and interrelations of biological macromolecules, e.g., polysaccharides, proteins, and nucleic acids; 2) correlation of physical properties of macromolecules in solution; 3) conformational properties of proteins and nucleic acids; and 4) aspects of metal ions in biological systems.

Topics at the interface of biology and computer technology will be discussed, including molecular sequence analysis, phylogeny generation, biomolecular structure simulation, and modeling of site-directed mutagenesis.

The cells and molecules of the immune system and their interaction and regulation; the cellular and genetic components of the immune response, the biochemistry of antigens and antibodies, the generation of antibody diversity, cytokines, hypersensitivities, and immunodeficiencies (i.e. AIDS); and transplants and tumors. Use of antibodies in currently emerging immunodiagnostic techniques such as ELISA, disposable kits, molecular targets, and development of vaccines utilizing molecular biological techniques, such as recombinant and subunit vaccines. Students (or groups of students) are expected to write and present a term project.