Examines the origins and the development of the short story in Turkish language, with references to the Western tradition. Investigates the structural and content characteristics of the short story as a genre. Places special emphasis on contemporary writers. The course is offered in Turkish.

Improved oral and written competence in Turkish; a more thorough knowledge and a better appreciation of linguistic/cultural heritage.

Classical thermodynamics: enthalpy, entropy, free energies, equilibria; introduction to statistical thermodynamics to describe the properties of materials; kinetic processes; diffusion of mass, heat, energy; fundamentals of rate processes in materials, kinetics of transformations.

The principles and computational methods to study the biological data generated by genome sequencing, gene expressions, protein profiles, and metabolic fluxes. Application of arithmetic, algebraic, graph, pattern matching, sorting and searching algorithms and statistical tools to genome analysis. Applications of Bioinformatics to metabolic engineering, drug design, and biotechnology.

Key aspects of microbial physiology; exploring the versatility of microorganisms and their diverse metabolic activities and products; industrial microorganisms and the technology required for large-scale cultivation.

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.

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

Topics will be announced when offered.

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.

An introduction to interactive Python and Jupyter Notebooks, Python built-in data structures, conditional statements, loops, functions, strings and basic input/output, basics of data manipulation and visualization with relevant Python libraries, different types of plots, vector/matrix representations, linear algebra operations, probability/statistics operations, data analysis applications

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.

Entropy, Relative Entropy and Mutual Information; Asymptotic Equipartition Theory; Entropy Rates of a Stochastic Process; Data Compression; Kolmogorov Complexity; Channel Capacity; Differential Entropy; The Gaussian Channel; Maximum Entropy and Spectral Estimation; Rate Distortion Theory, Network Information Theory.

Fundamental concepts of concurrency, non-determinism, atomicity, race-conditions, synchronization, mutual exclusion. Overview of parallel architectures, multicores, distributed memory. Parallel programming models and languages, multithreaded, message passing, data driven, and data parallel programming. Design of parallel programs, decomposition, granularity, locality, communication, load balancing. Patterns for parallel programming, structural, computational, algorithm strategy, concurrent execution patterns. Performance modeling of parallel programs, sources of parallel overheads.

Algorithms, models, representations, and databases for collecting and analyzing biological data to draw inferences. Overview of available molecular biological databases. Sequence analysis, alignment, database similarity searches. Phylogenetic trees. Discovering patterns in protein sequences and structures. Protein 3D structure prediction: homology modeling, protein folding, representation for macromolecules, simulation methods. Protein-protein interaction networks, regulatory networks, models and databases for signaling networks, data mining for signaling networks.

Entropy, Relative Entropy and Mutual Information; Asymptotic Equipartition Theory; Entropy Rates of a Stochastic Process; Data Compression; Kolmogorov Complexity; Channel Capacity; Differential Entropy; The Gaussian Channel; Maximum Entropy and Spectral Estimation; Rate Distortion Theory, Network Information Theory.

Introduction to Microsystems, MEMS and its integration with optics; Microfabrication and process integration; MEMS Modeling and design; Actuator and sensor design; Mechanical structure design; Optical system design basics; Packaging; Optical MEMS application case studies; Scanning systems (Retinal Scanning Displays, Barcode scanners); Projection display systems (DMD and GLV); Infrared imaging cameras; Optical switching for telecommunications.

Review of 2-D linear system theory and 2-D Fourier transforms. Integral transforms used in optical signal processing; Fundamentals of physical optics and diffraction theory; Fourier and imaging properties of optical systems; Coherent and Incoherent optical image processing; Fundamental architectures for correlation and spectrum analysis; Interferometry; Discrete analog optical processors; Holography; Review of 3D Display technologies.

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.

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.