[Bio-software] BCI summer school

Luca Bortolussi via bio-soft%40net.bio.net (by luca from dmi.units.it)
Wed May 30 09:41:28 EST 2012


Joint Second FVG International Summer School on Bioinformatics
Seventh International Summer School on
Biology, Computation and Information
BCI 2012


September 10-14, 2012, Udine, Italy




The School of Biology, Computation, and Information (BCI),
reaching this year its seventh edition, as a joint event
with the second FVG summer school on bioinformatics,
aims at bringing together Teachers and Students in
Biology, Mathematics, and Computer Science.
The main goal of the School is to
give an updated overview of interdisciplinary techniques
and problems cross-bordering the three fields.

This year's edition will be dedicated to the study of
interaction networks in biological systems, particularly on
genetic regulatory networks and biochemical networks.
The topics of the school will cover such issues as production of
experimental data, construction of mathematical and
computaional models, and statistical validation and
fitting of models agaist data.

The three distinguished speakers for this year's edition
are Bijoern Usadel (Biology), Vincent Danos
(Computer Science), and Guido Sanguinetti (Mathematics) and
the school will take place during the second week of
September (September 10-14, 2012).

A workshop will take place during the last day of the summer school,
while poster session will be organized throughout the conference.



Main topic: biological interaction networks


Area: Mathematics
Lecturer: Dr. Guido Sanguinetti,
University of Edinburgh, UK.

Bio: Guido Sanguinetti received his degree in Physics from the
University of Genova and his DPhil in Mathematics from the University
of Oxford. He was a postdoc, then lecturer, in the Department of
Computer Science at the University of Sheffield prior to joining
the faculty at the School of Informatics, University of Edinburgh,
in 2010. His interests focus on mathematical and statistical models
of dynamic biological systems.

Abstract: Uncertainty is inherent in many aspects of biology,
from the intrinsic noise of cellular reactions, to the extrinsic
noise due to fluctuating environments, to inevitable experimental
noise in the measurement process. Proper handling of uncertainty
is essential in many steps of model development. In these lectures,
I will review the mathematical foundations of stochastic modelling
and introduce some more advanced tools for statistical inference in
models of biological systems. I will introduce the basic concepts
of probability theory and focus on Bayes' theorem as a tool for
calibration and uncertainty quantification. I will explain some
concepts of statistical inference such as Markov chain Monte Carlo
and variational methods. I will then present some basic time-series
models and their use in biology, and conclude discussing more advanced
continuous time stochastic models.


Area: Computer Science
Lecturer: Prof. Vincent Danos,
University of Edinburgh, UK.

Bio: Vincent Danos graduated in Engineering, obtained a PhD in maths.
He has a 20 years academic career in logic and theoretical computer 
with an increasing concern for applications, mostly in formalising,
modeling and analysing complex systems—e.g., biomolecular networks.

Abstract: We will describe a new methodology to describe, simulate
and investigate complex biomolecular networks. This method is called
rule-based modelling and has the advantage that it can cope better with
combinatorial molecular systems than usual reaction-based methods.
The following aspects will be covered: knowledge representation,
simulation, causal analysis, model reduction techniques.


Area: Biology
Lecturer: Prof. Bijoern Usadel
RWTH Aachen University, Gernamy

Bio: Dr. Björn Usadel studied in Biochemistry in Berlin and New York
where he worked in Prof Ulrike Gaul's lab on the development on the
visual system of Drosophila. During this time he got interested in
Bioinformatics and then went on to Golm where he did his PhD in the
group of Dr. Markus Pauly on the identification and characterization
of novel cell wall genes. He then worked as a Postdoc in Prof. Mark
Stitt's lab on the visualization and evaluation of high throughput data.
After having been offered a Lecturership position within the Scottish
SULSA initiative he was offered his own group at the Max Planck Institute
and since then worked on data visualization, analysis as well as sugar
status and cell wall biosynthesis. Since 2011 he is a full pofessor at
the RWTH Aachen university and a co-director at the Forschungszentrum 

Abstract: The last decade has seen a massive explosion of omics data 
available to the individual researcher. Initially, the focus was on 
experiments focusing on the limited study of a certain condition. 
However, given
the massive growth of omics data in public data bases, these data can be
holistically integrated and novel inferences made. In the beginning this 
e.g. based on large scale approaches using simple correlation and a 
guilt by
association approach, having lead to a massive knowledge gain for 
Here we present several different streams of how to combine public (and 
dataset stemming from different disciplines in order to make new inferences
about the plant as a whole. Firstly we present a novel normalization method
for Affymetrix type microarrays beneficial for correlation analysis. We 
show how this normalized transcript data from focused areas can be used to
predict plant status which we validate using metabolite data. Based on 
models we combined metabolite and transcript data sets to make informed 
about gene knock-out experiments validating our predictions.
We also show that guilt by association approaches can be improved by 
novel measures, if a large data set is properly mined using expert 
rules. These
results also imply that the automatic incorporation of additional e.g. 
information will aid in data interpretation. As a proof of concept we 
show that
integration of sequence with simple microarray derived expression data 
leads to
an improved predictor for plant protein chloroplast import.
We finish by showing that next-generation sequencing data is not making 
more complicated but will allow us to get an even deeper understanding 
of living



A workshop, will take place during the last day of the summer school,
with title "Networks in Biology".
Invited speakers for the workshop are:
* Ezio Bartocci (TU Wien)
* Francesca Cordero (Università di Torino)
* Nicola Soranzo (CRS4 Bioinformatica, Pula, CA)

Participants of the School may submit an abstract for a
presentation during the workshop. Abstracts can be submitted
via the online submission system available at the school website,
and will be selected/judged by the Scientific Committee.



Registration deadline: 31 August.

We can provide accommodation for 40 participants,
assigned on a first-come first-served basis. To apply use
the online registration form available at school's website


Acceptance of more participants will be evaluated by the

Registration fee: EUR 100 (#)

The registration fee covers participation at all lectures,
course materials, coffee break, and lunches.
Accomodation is not included. Please contact the organization
or visit the web site for additional information.

(#) The registration is free for students and staff of the
University of Udine, University of Trieste, and SISSA.



The school will take place in Udine, in Friuli Venezia Giulia, Italy.
Lessons will be held at the congress center of ERDISU,
in Viale Ungheria, I-33100, Udine
The congress center is 15 minutes walking from the train station.



For all additional information, please visit the website:



- Regione Autonoma del Friuli Venezia Giulia
- University of Trieste.
- University of Udine.
- SISSA, Trieste.



- Alberto Policriti, University of Udine (school co-director)
- Luca Bortolussi, University of Trieste (school co-director)
- Claudio Altafini, SISSA, Trieste (school co-director)
- Nicola Vitacolonna, University of Udine


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