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Extra Form
Lecturer 김재경
Dept. KAIST
date Mar 24, 2016

The revolution of molecular biology in the early 1980s has revealed complex network of non-linear and stochastic biochemical interactions underlying biological systems. To understand this complex system, mathematical models have been widely used. In this talk, I will introduce the typical process of mathematical modelling including mathematical representation, model fitting to data, analysis and simulations, and experimental validation. Across each step of modelling process, I will also describe our efforts to develop a new mathematical tools and point to the parts of current toolbox of mathematical biology that need further mathematical development. Finally, I will present how mathematical modelling reveals the key mechanism underlying circadian clocks.   


Atachment
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  2. Towards Trustworthy Scientific Machine Learning: Theory, Algorithms, and Applications

  3. Toward bridging a connection between machine learning and applied mathematics

  4. Topology of configuration spaces on graphs

  5. Topology and number theory

  6. Topological surgery through singularity in mean curvature flow

  7. Topological Mapping of Point Cloud Data

  8. Topological aspects in the theory of aperiodic solids and tiling spaces

  9. Theory and applications of partial differential equations

  10. The significance of dimensions in mathematics

  11. The Shape of Data

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  13. The phase retrieval problem

  14. The Mathematics of the Bose Gas and its Condensation

  15. The Lagrange and Markov Spectra of Pythagorean triples

  16. The classification of fusion categories and operator algebras

  17. Symplectic topology and mirror symmetry of partial flag manifolds

  18. Symplectic Geometry, Mirror symmetry and Holomorphic Curves

  19. Symmetry Breaking in Quasi-1D Coulomb Systems

  20. Sums of squares in quadratic number rings

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