All Years Seminars
[INMA] 2011-04-05 (15.00) : Graph coverings and gossip coverage control
At Euler building
Speaker :
Frasca, Paolo
Abstract : Problems of unsupervised deployment of robotic networks and optimal partitioning of large complex environments are important
in engineering applications and open up interesting theoretical challenges. Classical techniques, based on Voronoi partitions, rely on two
assumptions: the environment to apportion is convex, and communication is synchronous and reliable along the edges of the Delaunay graph
induced by the robots' positions. In this talk I will present a novel solution which allows the robots to optimally deploy in non-convex
environments by using unreliable gossip communication. Joint work with R. Carli (University of Padova), J. W. Durham and F. Bullo (UCSB)
[INMA] 2011-03-29 (15.00) : A chain property for cube-scalar matrices of order 3
At Euler building
Speaker :
Jean-Pierre TIGNOL (UCL)
Abstract : Matrices a of order 3 such that a3 is a scalar matrix are the vertices of a directed graph in which an edge goes from a to b
when aba^{-1}b^{-1}= e^{2i\pi/3}. This talk will present a proof that any two cube-scalar matrices can be connected by a path of length at
most 4, using some exceptional algebraic structures.
[INMA] 2011-03-22 (15.00) : Temporal Discounting of Reward and the Cost of Time in Motor Control
At Euler building
Speaker :
Orban de Xivry, Jean-Jacques
Abstract : Why do movements take a characteristic amount of time, and why do diseases that affect the reward system alter control of movements?
Suppose that the purpose of any movement is to position our body in a more rewarding state. People and other animals discount future reward as a
hyperbolic function of time. In this presentation, I'll show that, across populations of people and monkeys, there is a correlation between discounting
of reward and control of movements. I'll consider saccadic eye movements and hypothesize that duration of a movement is equivalent to a delay of reward.
The hyperbolic cost of this delay not only accounts for kinematics of saccades in adults, it also accounts for the faster saccades of children,
who temporally discount reward more steeply. Our theory explains why saccade velocities increase when reward is elevated, and why disorders in the
encoding of reward, for example in Parkinson's disease and schizophrenia, produce changes in saccade. In addition, delay of reward elevates the cost
of saccades, reducing velocities. Finally, I'll consider coordinated movements that include motion of eyes and head and find that their kinematics is
also consistent with a hyperbolic, reward-dependent cost of time. Therefore, each voluntary movement carries a cost because its duration delays
acquisition of reward. The cost depends on the value that the brain assigns to stimuli, and the rate at which it discounts this value in time.
The motor commands that move our eyes reflect this cost of time.
[INMA] 2011-03-08 (15.00) : Democracy in Markov Chains and Its Preservation under Local Perturbations
At Euler building
Speaker :
Delvenne, Jean-Charles
Abstract : A sequence of irreducible Markov chains with increasing state
cardinality is called democratic if the sequence of corresponding
invariant probabilities converges to 0 uniformly. Democracy is a
relevant property which naturally shows up when we deal with distributed
algorithms like consensus or with opinion dynamic models: it says that
each agent measure/opinion is going to play a negligeable role in the
asymptotic behavior of the global system. Simple random walks on
undirected graphs of bounded degree and increasing cardinality are one
of the simplest examples of democratic chains. Similar examples can be
built considering more general time-reversible chains. In this paper we
prove a general result which says that, under some technical
assumptions, perturbing the transition probabilities from a finite
number of vertices of a time-reversible democratic sequence of chains,
democracy is preserved. We want to stress the fact that the local
perturbation in general breaks the time-reversibility of the chains. The
main technical assumption needed in our result is the irreducibility of
the limit Markov chains and we show with an example that this assumption
is indeed necessary.
[INMA] 2011-03-01 (15.00) : Analyzing the Whole Transcriptome by RNA-Seq data: Statistical and Computational Challenges
At Euler building
Speaker :
Claudia ANGELINI (Istituto per le Applicazioni del Calcolo "Mauro Picone", CNR)
Abstract : The main goal of the whole transcriptome analyses is to identify, characterize and catalogue all the transcripts expressed within a
specific cell/tissue - at a particular stage - with the great potential to determine the correct splicing patterns and the precise structure of genes,
and to quantify the differential expression of transcripts in both physiological and pathological conditions. Until 2004, hybridization and tag-based
technologies, such as microarray, have allowed researchers to obtain intriguing insights into human genetics, even though microarray techniques suffer
from background cross-hybridization issues and a narrow detection range, and tag-based approaches require laborious time- and cost-effective steps
for the cloning of fragments prior sequencing. Recently, the introduction of massively parallel sequencing on Next Generation Sequencing (NGS) platforms
has completely revolutionized the way of thinking in molecular biology.
Among the different application of NGS platforms, RNA-Seq is probably one of the most complex of the various sequencing protocols developed so far.
RNA-Seq has clear advantages over the existing approaches. First, RNA-Seq is not limited to the detection of known transcripts, thus allowing the
identification, characterization and quantification of new splice isoforms. In addition, it permits researchers to determine the correct gene annotation,
also defining the transcriptional boundaries of genes. Other advantages of RNA-Seq are the low "background signal", the absence of an upper limit
for quantification and consequently, the larger dynamic range of expression levels over which transcripts can be detected. RNA-Seq data also show high
levels of reproducibility.
In this seminar we will illustrate some of the computational tools available for the analysis of RNA-Seq data and discuss the main challenges to face
when analyzing RNA-Seq experiments. In particular we will focus on 1) Identification and quantification of transcriptional regions. 2) Identification and
quantification of isoforms. 3) Detection of differential expressed events between two or more experimental conditions. 4) Connection between RNA-seq
and ChIP-seq data.
Seminars
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