Recombinant DNA, enzymes and other biomolecules. Molecular genetics. Commercial use of microorganisms. Cellular reactors; bioseparation techniques. Transgenic systems. Gene therapy. Biotechnology applications in environmental, agricultural and pharmaceutical problems.
Drug design consists of identifying a target (DNA, RNA, proteins) that is known to cause a certain disease and selectively inhibiting or modifying its activity by binding a drug molecule to a specified location on that target. In this course, computational techniques for designing such a drug molecule will be taught. The topics to be covered are: Identification of the active part. Forces involved in drug-receptor interactions. Screening of drug libraries. Use of different software to determine binding energies. Identifying a lead molecule. Methods of refining a lead molecule for better suitability. Case studies: A survey of known drugs, success and failure stories.
Reconstruction of metabolic network from genome information and its structural and functional analysis, computational models of biochemical reaction networks; system biology in drug discovery and proteomics, flux balance analysis; modeling of gene expression; system biology in artificial intelligence. These concepts will be supported with statistic, thermodynamic, structural biology and learning machine
Modeling concepts and tools for chemical and biological systems. Steady state and transient modeling and simulation. MATLAB based case studies. Selected topics from the curriculum such as reaction stoichiometry, kinetics modeling, reactors, equation of state, phase equilibria, staged operations, fluxes, diffusion and convection, parameter estimation.
The fundamentals of tissue engineering at the molecular and cellular level; techniques in tissue engineering; problems and solution in tissue engineering; transplantation of tissues in biomedicine using sophisticated equipments and materials; investigation of methods for the preparation of component of cell, effect of growth factors on tissues.
Principles of molecular modeling in chemical engineering applications; fundamentals for molecular simulation of adsorption and diffusion processes in nanoporous materials; molecular dynamics methods for gas transport in nanopores; Monte Carlo methods for equilibrium based gas separations; molecular modeling of zeolites and metal organic frameworks for gas storage.
Independent research towards M.S. degree with thesis option.
Relationship between structure, function and dynamics in biomolecules. Overview of the biomolecular databases and application of computational methods to understand molecular interactions; networks. Principles of computational modeling and molecular dynamics of biological systems.
The following objectives will be met through extensive reading, writing and discussion both in and out of class.Build a solid background in academic discourse, both written and spoken. Improve intensive and extensive critical reading skills. Foster critical and creative thinking. Build fundamental academic writing skills including summary, paraphrase, analysis, synthesis. Master cohesiveness as well as proper academic citation when incorporating the work of others.
Optimization problems for dynamical systems. Pontryagin?s Maximum Principle. Optimality conditions for nonlinear dynamical systems. Linear Quadratic Optimal Control of continuous and discrete linear systems using finite and infinite time horizons. Stability and performance analysis of the properties of the optimal feedback solutions. Moving horizon optimal control of constrained systems using Model Predictive Control formulation. Applications from different disciplines and case studies.
Convex analysis, optimality conditions, linear programming model formulation, simplex method, duality, dual simplex method, sensitivity analysis; assignment, transportation, and transshipment problems.
Crystal structure, reciprocal lattice, determination of crystal structure by x-ray diffraction, energy levels of a periodic potential, Bloch theorem, band theory of solids, crystal defects, lattice vibrations and phonons; electrical conductivity, metals, dielectrics, and semiconductors; magnetic effects, paramagnets, diamagnets, ferromagnets, and superconductors; optical properties of materials, refractive index, dispersion, absorption and emission of light, nonlinear optical materials, high harmonic generation, Raman effect.
Thermal and mechanical properties of metals, polymers, ceramics and composites in relation to their structure & morphology; change in microstructural mechanisms and macroscopic behaviour with temperature; crystallization, melting & glass transition, stress-strain behaviour; elastic deformation, yielding, plastic flow; viscoelasticity; strengthening mechanisms, fracture, fatigue, creep
Intermolecular forces which govern self-organization of biological and synthetic nanostructures. Thermodynamic aspects of strong (covalent and coulomb interactions) and weak forces (dipolar, hydrogen bonding). Self-assembling systems: micelles, bilayers, and biological membranes. Computer simulations for ôhands-onö experience with nanostructures.
Interaction forces in interfacial systems; fluid interfaces; colloids; amphiphilic systems; interfaces in polymeric systems & polymer composites; liquid coating processes.
Materials for biomedical applications; synthetic polymers, metals and composite materials as biomaterials; biopolymers, dendrimers, hydrogels, polyelectrolytes, drug delivery systems, implants, tissue grafts, dental materials, ophthalmic materials, surgical materials, imaging materials.
Fabrication and characterization techniques for micro and nano electro mechanical systems, MEMS & NEMS (including: microlithography; wet & dry etching techniques; physical & chemical vapor deposition processes; electroplating; bonding; focused ion beams; top-down approaches - electron-beam lithography, SPM, soft lithography - ; bottom-up techniques based on self-assembly). Semiconductor nanotechnology. Nanotubes & nanowires. Biological systems. Molecular electronics.
Linear algebra: Vector and inner product spaces, linear operators, eigenvalue problems; Vector calculus: Review of differential and integral calculus, divergence and Stokes' theorems. Ordinary differential equations: Linear equations, Sturm-Liouville theory and orthogonal functions, system of linear equations; Methods of mathematics for science and engineering students.
Provides hands-on teaching experience to graduate students in undergraduate courses. Reinforces students' understanding of basic concepts and allows them to communicate and apply their knowledge of the subject matter.
Advanced nanostructured materials used in energy conversion and production, membrane electrode assemblies for fuel cells, photovoltaic devices, nanoporous materials for acoustic and thermal insulation, energy storage devices such as lithium ion batteries.
Advanced level thermodynamics, entropy, free energy, physical conversion of pure Materials and mixtures, phase rules and phase diagrams, chemical equilibrium, electrochemistry, chemical reaction rate, complex reaction kinetics, molecular reaction Dynamics, statistical thermodynamics, molecular structures.
This advanced course will help students to understand fundamental methods used for materials characterization. Students will learn principles and applications of detectors and amplifiers, optical spectroscopy, electron and scanning probe microscopy, X-ray diffraction, fluorescence and spectroscopic methods, surface analysis techniques. Students will be able to use the knowledge in the broad area of materials research. By the end of the course, the students will be able to choose appropriate methods for characterizing each specific type of materials and to treat and analyze the data obtained by such techniques.
Non-covalent interactions; molecular recognition; self-assembly; fluorescence and molecular devices; the chemistry, properties and application areas of major anion, cation or neutral molecule hosts such as crown ethers, cryptands, cucurbiturils, calixarenes and cyclodextrins; examples of artificial, self-assembled systems that are mimicking the important biological processes as well as some related studies from current literature.