QLS guest seminars - Monday 9 and Wednesday 11 October

[Quantitative Life Sciences]

*QLS  guest seminars  - Monday 9  and Wednesday 11 October
*ICTP, Central Area, 2nd floor, old SISSA building, Via Beirut*
*
*Monday 9 October at  14:30*

Title: Modeling vascular tumors

Speaker: Thierry Fredrich -  Universität des Saarlandes, Saarbrücken, 
Germany

Abstract:
Tumors appear in various types and affect a huge variety of functional 
aspects. We focus on the stage when the cluster of cancerous cells 
becomes larger than the average diffusion length of the required 
nutrients. At this point the tumor starts to modify the surrounding 
vascular structure of healthy tissue which is a complex and not yet 
understood process. Since the changes in topology and spatial 
arrangement of blood vessels and capillaries affect the distribution of 
interstitial fluid, oxygen, etc. this process is of special interest in 
order to understand cancer at malignant scales.

We use computer simulations to design artificial blood vessel networks 
followed by modeling vascular tumor growth. During this talk I will give 
you a brief overview of our model.

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*
Wednesday 11 October at 11:00*

Title: Automatic topography of complex data sets by accurate density 
estimation

Speaker: Alex Rodriguez - Statistical and Biological Physics, SISSA

Abstract:
Data sets can be considered an ensemble of realizations drawn from a 
density distribution. Obtaining a synthetic description of this 
distribution allows to rationalize the underlying generating process and 
building human-readable models. In simple cases, visualizing the 
distribution in a suitable low-dimensional projection is enough to 
capture its main features but real-world data sets are often embedded in 
a high-dimensional space.
I present a procedure that allows to obtain such a synthetic description 
in an automatic way with the only information of pairwise data distances 
(or similarities). This methodology is based on a reliable estimation of 
the intrinsic dimension of the dataset and the probability density 
function coupled with a modified Density Peaks clustering algorithm.
The final outcome of all this machinery working together is a 
hierarchical tree that summarizes the main features of the data set and 
a classification of the data that maps which of these features they 
belong to.

Everyone interested is most welcome to attend!

-- 
Erica Sarnataro
Group Secretary
Quantitative Life Sciences
The Abdus Salam International Centre for Theoretical Physics (ICTP)
Trieste,  Italy
Tel. +39-040-2240623
www.ictp.it/research/qls.aspx
e-mail: qls at ictp.it