Archived Course Catalog for Academic Year 2014 2015

Degree Completion Requirements for AY2014/2015

The OIST Graduate School offers an integrated doctoral program leading to the degree of Doctor of Philosophy (PhD). The degree of PhD is a research postgraduate degree. Such a degree shall be awarded to a candidate who

1. meets admission requirements and receives and accepts an offer of admission, and is registered as a full-time PhD student for a minimum of three years and not more than ten years; and
2. satisfactorily completes prescribed work amounting to at least 30 credits (20 from courses, 10 from research work) or alternatively, has obtained the equivalent number of credits based on prior study; and
3. presents a successful thesis representing the result of the candidates research which should constitute an original contribution to knowledge and contain material worthy of publication; and
4. satisfies the examiners in an oral examination in matters relevant to the subject of the thesis.

Note 1: credits based on prior study can be waived up to a maximum of 10 elective credits to recognise relevant prior learning, at the advice of the mentor and with approval of the graduate school. This is not a guarantee that such waiver will be made.

Note 2: a published paper or manuscript ready for publication from the research work presented in the thesis shall be appended to the examination version of the thesis to denote that the "material is worthy of publication".

Note 3: after successful examination of the written thesis, a thesis defence is conducted before two external examiners on-site in an oral exam.  A public presentation of the thesis is required, and takes place immediately preceding the closed examination.

Courses delivered AY2014/2015

A101 Adaptive Systems 

Detailed Content

1. Introduction: variety of learning and adaptation
2. Probability theory: entropy, information, Bayes theorem
3. Pattern classification
4. ​Function approximation
5. Kernel methods
6. Clustering, Mixture Gaussian, EM algorithm
7. Principal Component Analysis, Self-organizing map
8. Graphical models, Belief propagation
9. Sampling methods, Genetic algorithms
10. Kalman filter, Particle filter
11. Reinforcement learning, Dynamic programming
12. Decision theory, Game theory
13. Multiple agents, Evolutionary stable strategies
14. Communication and cooperation
15. Presentation and discussion

A102 Mathematical Methods of Natural Sciences 

A201 Quantum Mechanics

Detailed Content

A202 Fluid Dynamics 

Note: This course is designed for biologists rather than physicists.  Students must have completed Maths I and Maths II, or be able to demonstrate equivalent mathematical knowledge and expertise.

Detailed Content

A203 Advanced Optics 

Detailed Content

1. Ray and wave optics
2. Laser optics and Gaussian beams
3. Non-Gaussian beam optics 
4. Fourier optics 
5. Electromagnetic optics
6. Nonlinear optics
7. Lasers, resonators and cavities
8. Photon optics
9. Photon statistics and squeezed light
10. Interaction of photons with atoms 
11. Experimental applications: Optical trapping 
12. Experimental applications: Laser resonator design
13. Experimental applications: Light propagation in optical fibers and nanofibers
14. Experimental applications: laser cooling of alkali atoms
15. Review of classical optics
16. Laboratory Exercises:  Mach-Zehnder & Fabry-Perot Interferometry; Fraunhofer & Fresnel Diffraction; Single-mode and Multimode Fiber Optics; Polarization of Light; Optical Trapping & Optical Tweezers

A205 Quantum Field Theory 

Detailed Content

1. An electron in a uniform electromagnetic field: Landau levels
2. Canonical Quantization
3. Antiparticles
4. Particle decay
5. Feynman rules and the S-matrix
6. Weyl and Dirac spinors
7. Gauge Theories
8. Quantization of the electromagnetic field
9. Symmetry breaking
10. Path integrals
11. Aharonov-Bohm effect
12. Renormalization
13. Quantum chromodynamics
14. Nuclear forces and Gravity
15. Field unification

A206 Analog Electronics 

Detailed Content

1. Passive components. Current and voltage sources, Thevenin and Norton equivalent circuits. Diodes. (Ebers Moll equation)
2. The bipolar transistor, transconductance and its use in making efficient current and voltage sources.
3. Common emitter, common base, amplifiers. Differential amplifiers, current mirrors.
4. Push pull and other outputs, as well as some other useful circuits. Miller effect.
5. Thermal behavior of transistors; circuit temperature stability.
6. Field effect transistors and analog switches.
7. Operational Amplifiers and basic op amp circuits.
8. Negative feedback.
9. Sample and hold, track and hold, circuits. Further applications of op amps.
10. Filters
11. Voltage Regulators
12. Noise, noise reduction, transmission lines, grounding, shielding,
13. Lock in amplifiers.
14. Instrumentation amplifiers.
15. Analog to Digital conversion.

A207 Nanotechnology

Detailed Content

 1, 2. Introduction to Nanotechnology and its applications (2 lectures)
    History, State of the art nanotechnology, applications in different fields
    3, 4. Surface imaging and visualizations (2 lectures)
    SPM, SEM, TEM
    5, 6. Conventional Nanofabrication (2 lectures)
    Microfabrication, e-beam lithography, photolithography, micro and nanoelectronics
    7, 8. Non-conventional nanofabrication (2 lectures)
    Nanoimprint lithography, bottom top fabrication
    9 – 13. Nanomaterials: Synthesis, properties and application (5 lectures)
    Nanoparticles, nanorods, nanocrystals, nanobiomaterials , nanostructured thin films
    14, 15. Nanosystems and self-assembly (2 lectures)
    Self assembly of hybrid systems, bioorganic/inorganic inspired nanodevices               

A208 Bioorganic Chemistry

Detailed Content

1. Methods of chemical transformations to access designer molecules
2. Strategies for the development of new reaction methods including stereoselective reaction methods
3. Asymmetric reactions and asymmetric catalysis
4. Catalytic enantioselective reactions: Carbon-carbon bond forming reactions
5. Catalytic enantioselective reactions: hydrolysis, reduction, dynamic kinetic resolutions, etc.
6. Design and synthesis of functional molecules
7. Chemical mechanisms of bioactive molecules including chemistry of enzyme inhibitors
8. Molecular recognition and non-covalent bond interactions
9. Enzyme catalysis and catalytic mechanisms
10. Enzyme catalysis and small organic molecule catalysis
11. Enzyme kinetics and kinetics of non-enzymatic reactions
12. Strategies for the development of new designer catalysts
13. Methods in identification and characterization of organic molecules
14. Strategies for the development of designer functional proteins and peptides
15. Chemical reactions for protein labeling; chemical reactions in the presence of biomolecules

A209 Ultrafast Spectroscopy 

Detailed Content

1. Introduction, History and Development:
2. Basic Concepts
3. Understanding Ultrafast Pulses:
4. Spectrum, Fourier Transform, Uncertainty Principle, wavelength, repetition rate
5. Understanding Ultrafast Pulses & Capabilities:
6. Time Resolution, Nonlinearities,
7. Ultrafast pulse measurement: Spectrum, Phase, Amplitude, Intensity
8. Ultrafast pulse measurement: AutoCorrelation, FROG, SPIDER
9. Ultrafast Techniques: Pump Probe, Four-Wave Mixing, or others.
10. Ultrafast Techniques: Time Resolved Fluorescence, Up-converstion, or others.
11. Ultrafast Techniques: THz-TDS, Higher Harmonic Generation, or others.
12. Ultrafast Techniques: Single Shot Measurements, etc.
13. Applications: e.g. Condensed Matter Physics
14. Applications: e.g. Chemistry and Materials Science
15. Applications: e.g. Biology

A210 Advanced Quantum Mechanics 

Detailed Content

1. Quantum Mechanics: Mathematical Framework

2. Quantum Mechanical Postulates

3.  Quantum Measurements

4. Quantum Algorithms

5. Quantum Computing: Physical Realisations

6. Quantum Noise

7. Entropy and Information

8. Quantum Statistical Mechanics

9. Quantum Information Theory

A301 Signal Transduction 

Detailed Content

A303 Developmental Biology 

Detailed Content

 1. Basic concepts of developmental biology, and introduction of model systems
2. Development of the Drosophila embryonic body plan
3. Organogenesis
4. Patterning of vertebrate body plan
5. Morphogenesis
6. Cell fate decision in the vertebrate nervous system
7. Current topics of neuronal specification and multipotency of neural stem cells
8. Axon guidance, target recognition
9. Synaptogenesis
10. A model for neurodegeneration in Drosophila
11. Debate of topics of developmental biology by students
12. Debate of topics of developmental biology by students
13. Debate of topics of developmental biology by students
14. Genetic tools for live imaging of fluorescence-labeled cells using Drosophila
15. Genetic tools for live imaging of fluorescence-labeled cells using zebrafish

A304 Evolutionary Developmental Biology 

Detailed Content

    1 Introduction (background, general concepts, etc)
    2 History of animals (fossil records, phylogenic tree)
    3 History of animals (genomics, molecular phylogeny)
    4 Genetic toolkits (developmental concepts)
    5 Genetic toolkits (Hox complex)
    6 Genetic toolkits (genetic toolkits, animal design)
    7 Building animals (lower metazoans)
    8 Building animals (protostomes)
    9 Building animals (deuterostome and vertebrates)
    10 Evolution of toolkits (gene families)
    11 Diversification of body plans (body axis)
    12 Diversification of body plans (conserved and derived body plans)
    13 Evolution of morphological novelties
    14 Species diversification
    15 Phylum diversification   

A305 Microbiology and Biotechnological Applications 

Detailed Content

1. Introduction I (overview, main terms, systematics, taxonomy, main groups of prokaryotic (archaea, bacteria) and eukaryotic (protists, fungi) microorganisms, viruses)
    2. Introduction II (history of microbiological research and biotechnology, principal characteristics, evolutionary relationships, current questions and directions)
    3. Biochemistry and physiology of prokaryotes
    4. Biochemistry and physiology of eukaryotic microorganisms
    5. Comparative biochemistry and physiology (differences between microorganisms and higher eukaryotes), genetics of microorganisms
    6. Experimental and computational methods in microbiology
    7. Environmental microbiology and biogeochemical cycles I
    8. Environmental microbiology and biogeochemical cycles II
    9. Microorganisms in symbiosis
    10. Secondary metabolism, bioactive compounds, genome mining
    11. Biotechnology of enzymes
    12. Biodegradation and bioremediation
    13. Microorganisms as energy sources: biofuels and fuel cells
    14. Metabolic modeling and engineering I
    15. Metabolic modeling and engineering II                

A306 Neuroethology

Detailed Content

1. Introduction (Basic Neurophysiology and neuronal circuits)
2. Sensory information I: Visual and Auditory (map formation, plasticity and critical period, etc.)
3. Sensory information II: Olfactory (Chemical) and other senses
4. Sensory perception and integration I (Echolocation, Sound localization, etc.)
5. Sensory perception and integration II (Sensory navigation, etc.)
6. Motor control I (Stereotyped behavior)
7. Motor control II (Central pattern generator)
8. Sexually dimorphic behavior
9. Learning I (Learning and memory)
10. Learning II (Associative learning)
11. Learning III (Sensory motor learning during development)
12. Learning VI  (Spatial navigation)
13. Behavioral plasticity and the critical period
14. Recent techniques in neuroethology

A307 Molecular Oncology and Cell Signaling

Detailed Content

1. Historical background of molecular oncology
2. Viruses, chemical carcinogens, and tumor development
3. RNA tumor viruses and oncogenes
4. Discovery of anti-oncogenes
5. Regulation of signal transduction and cell cycle progression by oncogenes and anti-oncogenes
6. Roles of oncogenes and anti-oncogenes in normal physiology
7. Molecular mechanisms of metastasis
8. Genome, proteome, metabolome, and cancer
9. Animal models of cancer
10. Drug development for cancer treatment
11. Cancer stem cells
12. microRNA and cancer development
13. Genome sciences in cancer research
14. Systems biology in cancer research

A308 Epigenetics 

Detailed Content

1. Introduction to Epigenetics
2. Histone variants and modifications
3. DNA methylation
4. RNA interference and small RNA
5. Regulation of chromosome and chromatin structure
6. Transposable elements and genome evolution I
7. Transposable elements and genome evolution II
8. Epigenetic regulation of development I
9. Epigenetic regulation of development II
10. Genome imprinting
11. Dosage compensation I
12. Dosage compensation II
13. Epigenetic reprogramming and stem cells
14. Epigenetics and disease 
15. Epigenomics

A309 Quantitative Molecular Biology 

Detailed Content

1. Introduction and general aims. Classic study organisms (pros and cons for quantitative analysis)
2. Basic lexicon and laboratory navigator I
3. Laboratory navigator II
4. Extraction / purification techniques. Gel electrophoresis and detection.
5. Hybridization techniques
6. Immunostaining and immunoprecipitation techniques
7. Sequencing techniques
8. Microarrays
9. Mass spectrometry
10. Microscopy essentials
11. Flow cytometry and cell sorting
12. Topics in gene expression
13. Inducible systems vs. repressible systems. Construction of gene circuits
14. Synthetic Biology topics I and II.

Requires B06 Cell Biology (or knowledge of gene regulation processes, cell division and recombinant DNA) and B03 Mathematics I  (or higher, preferably).

Ideally taken with A301 Signal Transduction

A310 Computational Neuroscience                           

Detailed Content

1. Introduction and the NEURON simulator
2. Basic concepts and the membrane equation
3. Linear cable theory and passive dendrites
4. Synapses and passive synaptic integration
5. Ion channels and the Hodgkin-Huxley model
6. Neuronal excitability and phase space analysis
7. Exercise evaluations and discussion of student selected modeling papers
8. Reaction-diffusion modeling and calcium dynamics
9. Active dendrite modeling and parameter searching
10. Integrate-and-fire neurons and network modeling
11. Oscillations and microcircuit modeling
12. Large-scale network modeling
13. Exercise evaluations and discussion of student selected modeling papers

Requires prior B03 Mathematics I, B04 Mathematics II and B05 Neurobiology or similar background knowledge

A401 Controversies in Science 

Detailed Content

1. The Scientific Method, Ockham's Razor, Basic Philosophy of Science

A402 Computational and Mathematical Biology 

Detailed Content

• Day 1 (10)  Introduction / Theory. Protein, Enzyme kinetics, Enzymes kinetic (Goryanin)/ Practicals. Introduction, installing software (Goryanin/Sorokin) 
• Day 2 (11)   Theory: Metabolic Pathways. Graph analysis of Biological   networks. Standards in Systems Biology(Goryanin)/ Practicals. Cytoscape. SBGN. Analysis and reconstruction of metabolic networks (Goryanin/Sorokin) 
• Day 3 (12)  Theory: Flux Balance Analysis. Stoichiometric matrix and its properties. Extreme pathways (Sorokin)/ Practicals. FBA with pyCOBRA. Modeling of mutations and environment changes(Goryanin/Sorokin) 
• Day 4 (13)  Theory: Stochastic reaction modelling. Gillespie algorithm. Tau-leaping. Rule-based modelling. Static and dynamic analysis of rule-based models. (Sorokin) /Practicals. Simulation with Gillespie algorithm. Modelling with KaSim and SpatialKappa. (Goryanin/Sorokin) 
• Day 5 (14)   Theory:  Applications in Systems Biology. (Goryanin). Practicals. Tests (Goryanin/Sorokin) 
• Day 6 (17)  Introduction to Signaling (Kitano)
• Day 7 (18)  Cell Cycle (Kitano) 
• Day 8 (19)  Simulation Modeling Hands-on (Physiological Modeling by Dr. Asai) (Kitano) 
• Day 9 (20)  Simulation Modeling Hands-on & Systems Analysis and their biological implications --  Wrap up (Kitano) 

A403 Structural Biology: Protein Xray Crystallography  

Detailed Content

1. Introduction to protein folding
2. Principles of protein purification
3. Principles of protein crystallization
4. Protein characterization
5. Principles of X-ray crystallography
6. Bioinformatics tools      

A404 Measurement 

Detailed Content

1. Information theory: signals, background and noise.
2. Probability, distributions, Gaussians, Boltzmanns
3. Sample size and Power of analysis
4. Signal sampling techniques
5. Frequency and digitization
6. Fourier and other transforms
7. Instrumentation
8. Amplifiers
9. Modulation
10. Time-locked measurements, synchronous and asynchronous events
11. Analog instruments
12. Noise reduction
13. Small signals
14. Projects
15. Projects

A405 Emerging Technologies in Life Sciences 

Detailed Content

1. Course Introduction & Nucleotide sequencing I (Background, Basics, PCR & qPCR, etc)
2. Nucleotide sequencing II (Next generation, Genome analysis, etc)
3. Nucleotide sequencing III (RNA sequencing, ChIP, Applications, etc)
4. Microarray I (Background, Basics, DNA chips, etc)
5. Microarray II (Protein chips, Applications, Future development, etc)
6. Confocal laser scanning microscopy I (Basics, Live cell imaging, probes, etc)
7. Confocal laser scanning microscopy II (Multi-color imaging, Multi-photon, etc)
8. Confocal laser scanning microscopy III (Spectral imaging, FRAP, FRET, etc)
9. Confocal laser scanning microscopy IV (PALM, SHIM, STED, etc)
10. Microfluidics I (Background, Basics, Microfabrication, etc)
11. Microfluidics II (Applications, Devices, Future development, etc)
12. Single molecule imaging I (FCS, FCCS, etc)
13. Single molecule imaging II (TIRF、FLIM, etc)
14. Neuroimaging I (Optical, PET/CT, etc)
15. Neuroimaging II (MRI/fMRI, SPECT, etc)

A409 Electron Microscopy 

Detailed Content

1. History of the TEM / Design of a TEM - Lecture
2. Design of a TEM (cont’d) -  Lecture
3. Design of a TEM (cont’d) -  Lecture
4. Demonstration of a TEM - Demo
5. Math refresher / Electron waves - Lecture
6. Fourier transforms - Lecture
7. Intro to image processing software in SBGRID - Practical
8. Image alignment - Practical
9. Contrast formation and transfer -  Lecture
10. Image recording and sampling - Student presentation
11. Applications in biology - Lecture
12. Preparation of biological samples -  Demo
13. Low-dose cryo-EM - Student presentation
14. 2D crystallography - Student presentation
15. Overview of the single particle technique -  Lecture
16. Review of theory - Lecture
17. Electron tomography (guest lecture) - Lecture
18. Physical limits to cryo-EM - Student presentation
19. Particle picking -  Practical
20. Classification techniques -  Student presentation
21. 3D reconstruction - Student presentation
22. Image processing project 1 - Practical
23. Resolution-limiting factors -  Student presentation
24. Refinement and sources of artifacts -  Student presentation
25. Image processing project 2 - Practical
26. A sampling of original literature - Discussion

A410 Molecular Electron Tomography 

Detailed Content

1. Learning the computer 1
2. Learning the computer 2
3. Practical Aspect of sample preparation for cryo-TEM
4. Sample preparation for cryo-TEM
5. Sample preparation for cryo-TEM; data collection
6. 3D reconstruction 1
7. 3D reconstruction 2
8. 3D reconstruction 3
9. Generating simulation-data
10. 3D reconstruction from simulation-data 1
11. 3D reconstruction from simulation-data 2
12.  Electron Microscopy: Sample Preparation

B02 Biology 

Detailed Content

1. Gene and genome structure

B03 Mathematics I 

Detailed Content

1 History of mathematics and relation to natural sciences.

B04 Mathematics II 

Detailed Content

    1. Linear Algebra: Rotations in the plane and space. Matrix representation. Matrix multiplication.
    2. Linear Algebra: Solution of linear systems. Eigenproblems. Hardy-Weinberg equilibrium.
    3. Linear Algebra: Change of basis, discrete Fourier transform.
    4. Continuous flows: Vector fields, conservation of mass, compressibility and divergence.
    5. Exercises (individual)
    6. Systems of differential equations: Reduction to systems of first order. Euler’s method.
    7. Systems of differential equations: Reaction-diffusion equations. Heun’s method.
    8. Systems of differential equations: Hodgkin-Huxley equations.
    9. Dynamical Systems: Linear systems, fixed points.
    10. Dynamical Systems: Linearization of nonlinear systems.
    11. Dynamical Systems: Predator-prey systems. Bifurcation. Chaos.
    12. Stochastic differential equations: Euler-Maruyama method.
    13. Student presentations: Preparation.
    14. Student presentations: Preparation.
    15. Student presentations: Presentation.

B05 Neurobiology 

Detailed Content

1. May-13 Introduction to the course and its subject  Arbuthnott
2. May-20 Ionic basis of excitability and voltage-gated ion channels Arbuthnott
3. May-27 Action potential generation and propagation Baughman
4. Jun-03 Synaptic transmission, neurotransmitters, neuromodulators Arbuthnott
5. Jun-10 Synaptic ion channels and receptors Arbuthnott
6. Jun-17 Synaptic plasticity, intracellular signaling, retrograde messengers Arbuthnott
7. Jun-24 Neural morphology, cytoskeleton, and implications for function Baughman
8. Jul-01 Neural networks, cerebral cortex, basal ganglia, cerebellum Arbuthnott
9. Jul-08 Motor system; movement Arbuthnott
10. Jul-15 Somatosensory systems; Whiskers Arbuthnott
11. Jul-22 Mechanism of sensory transduction Baughman
12. Jul-29 Sensory systems Vision and hearing Baughman
13. Aug-5 Discussion of neurophysiology of brain systems with methods in the awake animal Arbuthnott

B06 Cell Biology and Genetics 

Detailed Content

1. Mendelian genetics
2. Recombination, linkage and mapping
3. Gene interaction, complementation, and epistasis
4. Nucleic acids and chromosome structure
5. Protein structure and function
6. DNA replication
7. Transcription and its regulation
8. mRNA splicing and translation 
9. Maintenance of genomic integrity 
10. Cellular structures and organelles 
11. Intracellular membrane trafficking 
12. Cell cycle and cell division 
13. Cellular cytoskeleton and cell movement 
14. Cell-cell communication 
15. Apoptosis 

B07 Statistical Methods 

Detailed Content

 Part I (May 12-21 by Nick Luscombe)

1 Introduction: goals of statistics
2 Confidence interval
3 Binomical, Gaussian, and log-normal distributions
4 P-value and t-test

Part II (May 26 - June 25 by Kenji Doya)
5 Probability distributions
6 Joint distribution, conditional distribution, correlation, and statistical dependence
7 Multiple testing and ANOVA
8 Linear models and Maximum likelihood estimate
9 Regularization and Bayesian methods

Part 3 (July 7 - 23 by Greg Stephens)
10 Entropy and Information theory
11 Principal component analysis
12 Stochastic process

B08 Physics for Life Sciences 

B09 Learning and Behavior

Detailed Content

1. Research methods (I)
2. Ethics
3. Hypothesis testing
4. Dependent and independent variables
5. Reliability and validity
6. Bias, blinding
7. Research methods (II)
8. Data collection methods
9. Observation
10. Surveys
11. Experimental and quasi experimental designs
12. Data analysis
13. Learning and behavior (I)
14. Classical, Pavlovian, respondent conditioning (elicited responses)
15. Operant, instrumental conditioning (instrumental responses)
16. Learning and behavior (II)
17. Reinforcement and punishment
18. Operant schedules
19. Learning and behavior (III)
20. Behavior modification
21. Applications
22. Motivation and reward
23. Drug addiction
24. ADHD
25. Memory and cognition (I)
26. Memory and cognition (II)
27. Perception and attention
28. Behavioral neuroscience (I)
29. Behavioral neuroscience (II)
30. Genes and behaviour
31. Animal models
32. Life span

B10 Analytical Mechanics 

Detailed Content

1. The Principle of Least Action

B11 Classical Electrodynamics 

Detailed Content

1. Charge and Gauss's Law
2. Current and Ampere's Law
3. Divergence and Rotation
4. Induction
5. Capacitance and Inductance
6. Maxwell's Equation 1
7. Maxwell's Equation 2
8. Vector and Scalar Potentials
9. Electromagnetic Waves
10. Energy, Dispersion
11. Impedance Concept
12. Reflection and Matching Condition
13. Relativistic Equation of Motion
14. Radiation from a Moving Charge
15. Synchrotron Radiation

B12 Statistical Physics 

B13 Theoretical and Applied Fluid Mechanics 

Detailed Content

1.  Overview of fluid mechanics
2.  Kinematics of flow 
3.  Review of Tensors and the Stress Tensor
4.  Conservation Laws: Mass, Momentum, and Energy
5.  Constitutive Equations: the Navier-Stokes Equations, Boundary Conditions.
6.  Potential Flows
7.  Vortex motion
8.  Dimensional analysis and similarity
9.  Exact solutions of viscous flows
10.  Creeping Flows 
11.  Boundary Layers
12.  Hydrodynamic Stability
13.  Turbulent flows

B14 Theoretical and Applied Solid Mechanics 

Detailed Content

 (1) Mathematical Preliminaries:

• Summation convention, Cartesian, spherical, and cylindrical coordinates.
• Vectors,  tensors,  linear operators, functionals.
• Eigenvalues and eigenvectors of second-order symmetric  tensors, eigenvalues as extrema of the quadratic form. 
• Fields, vector and tensor calculus.

 (2) Stress, Strain, Energy, and Constitutive Relations:

• Cauchy stress tensor, traction, small strain tensor, compatibility.
•  Strain energy, strain energy function, symmetries, elastic modulii.

(3) Elasticity and the Mechanics of Plastic Deformation:

• Navier equations, problems with spherical symmetry and problems with cylindrical symmetry (tunnels, cavities, centers of dilatation). 
• Anti-plane shear.  Plane stress, plane strain.
• The Airy stress-function method in polar and Cartesian coordinates.
• Superposition and Green's functions.
• Problems without a characteristic lengthscale.
• Flamant's problem, Cerruti's problem, Hertz's problem.
• Load-induced versus geometry-induced singularities (unbounded versus bounded energies).
• Problems with an axis of symmetry. 
• Disclinations, dislocations, Burgers vector, energetics;  relation to plastic deformation in crystalline solids.

(4) Fracture Mechanics:

• The Williams expansion, crack-tip fields and opening displacements via the Airy stress-function method (modes I, II) and via the Navier equations (mode III),  crack-tip-field exponents as eigenvalues,  stress intensity factors.
• Energy principles in fracture mechanics,  load control and displacement control. 
• Energy release rate and its relation to the stress intensity factors, specific fracture energy, size effect, stability. The Griffith crack and the Zener-Stroh crack. Anticracks.

(5) Possible Additional Topics (if time allows):

•  Elasticity and variational calculus, nonconvex potentials, two-phase strain fields, frustration, microstructures. 
•  Stress waves in solids, P, S, and R waves, waveguides,  dispersion relations, geophysical applications.
•  Dislocation-based fracture mechanics, the Bilby-Cotterell-Swindon solution, small- and large-scale yielding, T-stress effects,  crack-tip dislocation emission, the elastic enclave model.
•  Deterministic versus statistical size effects in quasibrittle materials.
•  Vlasov beam theory, coupled bending-torsional instabilities. 
•  Dynamic forms of instability, nonconservative forces, fluttering (Hopf bifurcation). 

B15 Immunology 

Detailed Content

1. Basic concepts in immunology
2. Innate immunity
3. Antigen recognition by B-cell and T-cell receptors
4. The generation of lymphocyte antigen receptors
5. Antigen presentation to T lymphocytes
6. Signaling through immune system receptors
7. The development and survival of lymphocytes
8. T cell-mediated immunity
9. The humoral immune response
10. Dynamics of adaptive immunity
11. The mucosal immune system
12. Failures of host defense mechanism
13. Allergy and Hypersensitivity
14. Autoimmunity and Transplantation
15. Manipulation of the immune response

B16 Ecology and Evolution 

Detailed Content

1. Introduction, levels of organization in biological systems.
2. Taxonomy, systematics, phylogenetics.
3. Biodiversity
4. Energy flows and transformations in biological systems.
5. Genomics and Genetics of Adaptation
6. Physiological ecology.
7. Population dynamics and regulation
8. Life histories
9. The evolution of sex and the evolution of cooperation
10. Community Ecology
11. Ecosystem Ecology
12. Global Climate system and Climate change
13. Conservation Biology

PD1 Professional Development I for 2014 Students

Detailed Content

Term 1 Module: Research conduct and ethics

• laboratory procedures, conduct and safety
• record keeping and data management
• plagiarism
• research misconduct
• authorship
• peer review
• conflicts of interest
• research with animals
• research with human subjects

Other Courses: Special Topics

States and Properties of Matter
Professor Mahesh Bandi 

Assessment
There will be regular assignments that include traditional problem sets and the study and critique of seminal scientific articles. There is no exam for the course. All Assessment is based on homework assignments.

Description
This is a series of four special topics courses presented over two terms (two courses per term). It treats the standard (gases, liquids and solids) and few exotic (polymers and colloids) classical states of matter, and explains how these states and their bulk properties emerge from the few interatomic and intermolecular forces at play. The emphasis is on developing strong physical intuition for microscopic mechanics using the simplest models that illuminate the concept. In doing so, we explain both the strengths and shortcomings of these simple models, and in particular, analyse the limiting conditions where they fail. Therefore, rather than theoretical rigour, the focus of the treatment is on performing quick order-of-magnitude calculations. As a result, although the mathematics is unsophisticated, Calculus is a pre-requisite. Wherever possible, scientific facts will be connected with the seminal experiments that established them.

Aim
An interdisciplinary course that explains emergence of bulk properties/behavior in materials from the few attractive and repulsive interatomic/molecular forces.

Resources
Text Book:
There is no prescribed textbook for this course. Lectures will be based on notes developed from diverse sources.

Reference Book:  
There is no prescribed textbook for this course. Lectures will be based on notes developed from diverse sources.

Basic Computing for Life Sciences
Coordinator: Professor Alexander Mikheyev

Aim: Introduce fundamentals of programming, databases and statistical analysis to students with minimal computational background.

Description: This is a basic introduction to programming, data storage and analysis for students with no prior computational experience. The course will be largely self-paced with ‘lectures’ in the form of ipython notebooks. The students will ultimately write a program to mine data from online databases, store it in a local SQL database and perform a large-scale statistical analysis, presenting the final data in an easy to read report. In the course of getting there, student will learn how to write computer programs in python, how to handle various data structures, and the basics of statistical analysis. Most of the course will involve the students in solving problems posed by the instructor, instead of actual lectures. The instructor’s role will be to guide students when they are stuck and to provide feedback on solutions. Students should expect about five to eight hours of week of work at a pace of their own choosing, although it can take more time. 

Course contents:

1. Getting everything installed, working with the command line, file and directory structure
2. Introduction to python
       Variables, and memory
       Data structures, loops, control statements
       Commenting and storing code
3. Debugging code
4. Efficiency of computer code
        Parallelizing your code
        Basics of cluster computing
5. Introduction to biopython
         Working with sequence data
         Mining data from on-line databases
6. Storing data
        Introduction to SQL
        Indexing databases
        Interfacing between SQL and other languages
7. Introduction to the R package
8. Visualizing data using ggplot
9. Linear models
10. Bootstrap and simulation
11. Putting it all together into one pipeline: Making reports in knitR