future
2011
all

# All seminars

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Arno Klein:
Topological methods in neuroscience

25 Feb 2011 11:15 a.m. in room 383 N

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Primoz Skraba:
Analyzing Dynamical Systems with Computational Topology

25 Mar 2011 11 a.m. in room 380 D

Analyzing systems is a difficult problem that is often made much
easier by a good choice of parametrization. A natural choice for
dynamical systems is the mapping to the circle. This mapping can
describe a variety of behaviour including (quasi)-periodicity and
recurrence. This talk will introduce a topological approach for
understanding dynamical systems from measurements. Starting with a
time series measurement of a dynamical system, using a pipeline based
in the framework of computational topology, we can recover an
astonishing amount of information about the system. We begin by
embedding the time series in a higher dimension and use persistent
cohomology to construct a natural parameterization which makes further
analysis much easier. I will discuss the individual components of the
pipeline as well as show results on several examples of synthetic and
real data.

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Caroline Uhler:
Chromosome packing in cell nuclei
(Berkeley)

22 Apr 2011 10:30 a.m. in room Gates 392

During most of the cell cycle each chromosome occupies a roughly spherical domain called a chromosome territory. Chromosome territories can overlap and their radial and relative positions are non-random and similar among similar cell types. A chromosome arrangement can be viewed as a packing of overlapping spheres of various sizes inside an ellipsoid, the cell nucleus. We present a non-convex model for chromosome arrangements and are particularly interested in the resulting number and volume of internal 'holes', which make chromosomes deep inside accessible to regulatory factors.

3 Oct 2011 4:15 a.m. in room 380-380C (ICME Colloquium)

An important aspect of understanding large and complex data sets is the large scale organization, or the shape, of the data. Topology is a mathematical discipline whose explicit goal is the study of shape. It constructs for representing shape in compressed, combinatorial manners, and also provides methods for measuring shape, where the notion of measurement is suitably defined. Topological methods have recently been adapted to for the study of finite samples from shapes. I will discuss these methods, with examples.

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Mikael Vejdemo Johansson:
Mayer-Vietoris methods in computational topology
(St. Andrews)

28 Oct 2011 11 a.m. in room 383-N