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|
Daily
schedule
| Time
|
Location
|
|
| 7:30-8:30am
|
Cappuccini or Miravalle
|
Breakfast
|
| 9:00-10:30am
|
Cappuccini
(lecture hall)
|
First
lecture
|
| 10:30-11:00am
|
|
Coffee
break
|
| 11:00am-12:30pm
|
Cappuccini
(lecture hall)
|
Second
lecture
|
| 12:30-2:00pm
|
Cappuccini
|
Lunch
break
|
| 2:00-3:30pm
|
Cappuccini
(lecture hall)
|
Third
lecture
|
| 3:30-4:00pm
|
|
Coffee
break
|
| 4:00-5:30pm
|
Cappuccini
(lecture hall)
|
Forth
lecture
|
| 5:30-7:30pm
|
|
Free
time
|
| 7:30pm
|
Cappuccini
|
Dinner
|
| 9:00pm
|
Cappuccini (poster hall)
|
Evening
poster sessions
|
Scientific program
| Sunday,
September 30
|
| 1pm-7pm
|
Arrival
|
| 8pm
|
Reception
dinner
|
| Monday,
October 1st
|
| 9:00am
|
D. Geiger
|
Inference in Bayesian networks
|
| 11:00am
|
D. Geiger
|
Learning Bayesian networks with applications to
bioinformatics
|
| 2:00pm
|
P. Frasconi
|
Introduction to neural networks and machine learning
|
| 4:00pm
|
P. Frasconi
|
Connectionist models for learning in sequential and
structured domains
|
| Tuesday,
October 2nd
|
| 9:00am
|
R. Shamir
|
Elementary Introduction to Molecular Biology
|
| 11:00am
|
S. Muggleton
|
Knowledge-mining in biological and chemical domains
|
| 2:00pm
|
D. Haussler
|
Overview of the Human Genome Project and the Construction
of the Working Draft
|
| 4:00pm
|
D. Haussler
|
Exploring the Working Draft of the Human Genome
|
| Wednesday,
October 3rd
|
| 9:00am
|
B. Schoelkopf
|
SVMs and kernel methods for high-dimensional data
|
| 11:00am
|
R. Casadio
|
Functional genomics and proteomics in silico
|
| 2:00pm
|
L.
De Raedt
|
Molecular Feature Mining in
HIV data
|
| 4:00pm
|
|
Workshop on AI methods
|
| Thursday,
October 4th
|
| 9:00am
|
P. Baldi
|
Protein Structure Prediction
|
| 11:00am
|
S. Brunak
|
Computational proteomics
|
| 2:00pm
|
R. Casadio
|
Fishing and modeling membrane proteins
|
| 4:00pm
|
R. Casadio
|
Ab-initio prediction of protein structures with contact
maps
|
| Friday,
October 5th
|
| 9:00am
|
B. Rost
|
Evolution teaches to predict protein structure and function
|
| 11:00am
|
B. Rost
|
The gory details of protein secondary structure prediction
|
| 2:00pm
|
S. Brunak
|
Prediction of orphan protein function
|
| 4:00pm
|
A. Apostolico
|
Computational
Theories of Surprise 1: A
Pattern Discovery Primer
|
| Saturday,
October 6th
|
| 9:00am
|
A.
Apostolico
|
Computational
Theories of Surprise 2: Algorithmics of Pattern Discovery and
Classification
|
| 11:00am
|
P. Baldi
|
DNA Structure, DNA Microarrays, Gene Regulation and
Regulatory Regions
|
| 2:00pm
|
A.
Valencia
|
Sequence
Based Prediction Methods
|
| 4:00pm
|
A.
Valencia
|
Interaction
Networks
|
| Sunday,
October 7th - Break day (Free time)
|
| Monday,
October 8th
|
| 9:00am
|
R. Serra
|
Introduction to genetic networks
|
| 11:00am
|
M. Gelfand
|
Recognition of regulatory signals 1. Traditional algorithms
|
| 2:00pm
|
M. Gelfand
|
Recognition of regulatory signals 2. Comparative methods
|
| 4:00pm
|
D.
Gilbert
|
Clustering proteins by fold
patterns
|
| 9:00pm
|
Poster
session 1
|
| Tuesday,
October 9th
|
| 9:00am
|
R. Shamir
|
DNA chips and analysis of gene expression
|
| 11:00am
|
R. Shamir
|
Problems and algorithms in reconstruction of gene networks
|
| 2:00pm
|
N. Kolchanov
|
Computer analysis of regulatory genomic sequences I
|
| 4:00pm
|
N. Kolchanov
|
Computer analysis of regulatory genomic sequences II
|
| 9:00pm
|
Poster session 2
|
| Wednesday,
October 10th
|
| 9:00am
|
M. Vendruscolo
|
Protein folding using contact
maps and contact vectors
|
| 11:00am
|
A. Covacci
|
Whole genome microarray for genetic diversity and
pathogenic signatures
|
| 2:00pm
|
H. Mueller
|
Near genome wide expression pattern analysis of the pRB
tumor suppressor pathway
|
| 4:00pm
|
R. Serra
|
Tumors as complex systems: In vitro generation of
transformation foci
|
| Thursday,
October 11th (Papers submitted by participants)
|
| 9:00am
|
M.
Embrechts
|
Data Strip Mining for the
Virtual Design of Pharmaceuticals with Neural Networks
|
| 9:30am
|
G.
Valentini
|
Recognition of Human Lymphoma
using Support Vector Machines, Multi-Layer Perceptrons and Gene
Expression Data
|
| 10:00am
|
H.
A. Kestler
|
Cluster analysis of
comparative genomic hybridization data
|
| 11:00am
|
D.
Lipson
|
Designing Specific
Oligonucleotide Probes for the Entire S. cervisiae Transcriptome
|
| 11:30am
|
P.
Cull
|
Improved Parallel and
Sequential Walking Tree Methods for Biological String Alignments
|
| 12:00am
|
P.
Juvan
|
Web-Enabled Abductive
Inference of Genetic Networks
|
| Friday,
October 12th
|
| 9am-12am
|
Departure
|
Posters
Poster
Session 1
|
|
PS
1 A.S.
Brok-Volchansky, A.A. Deev, and O.N. Ozoline
E.coli promoters annotation in terms of non-canonical elements.
Borders of promoter DNAs, presence of direct and inverted repeats.
|
|
PS
2 E.
Eskin and P. Pevzner
Discovering Dyad Signals with Exhaustive Pattern Search
|
|
PS
3 D.
Caffrey
A method to predict residues conferring functional differences
between related proteins
|
|
PS
4 I.
Artamonova , T. Gorodentseva and E. Sverdlov
Long terminal repeats of human endogenous retroviruses (K family)
and their distribution in human genome.
|
|
PS
5 G.
Thijs, K. Marchal, M. Lescot, S. Rombauts, B. De Moor, P. Rouze,
Y. Moreau
Extending the Gibbs sampling algorithm for motif finding with
higher-order background models
|
|
PS
6 S.
J. Anastasoff, T. Bao, J. A. Nelson
Genetic Algorithm Based Biological Simulations – A GA Model of
Mutation and Evolvability
|
|
PS
7 T.
S. Larsen
Procaryotic Gene finding
|
|
PS
8 M.
G. Kann and R. A. Goldstein
Performance evaluation of a new algorithm for the detection of
remote homologs with sequence comparison
|
|
PS
9 G.
Grant, E. Manduchi, S. Sokolovsky, and C. Stoeckert
Performance testing of methods for prediction of differentially
expressed genes from array data
|
|
PS
10 S.
Shen-Orr, R, Milo, and U. Alon
Exploring Escherichia coli transcriptional regulation - Discovering
design motifs
|
|
PS 11
B. Chor, S. Snir, Z. Yakhini, E. Yeger-Lotem
SB(H+RE) - Sequencing by Hybridization and Restriction Enzymes
|
Poster
Session 2
|
|
PS
1 I.
Ben-Gal and A. Shmilovici
Identifying Promoters by VOM Modeling
|
|
PS
2 A.
Micheli
QSAR and Drug Design by Neural Network for Structures
|
|
PS
3 T.
Davison
Using Support Vector Machines for the Classification of Data Quality
in Microarray Experiments
|
|
PS
4 A.G.
Vitreshchak
Computer analysis of regulation of genes, encoding aminoacyl-tRNA
synthetases and amino acid biosynthetic proteins in Gram positive
bacteria: T-box RNA regulatory element. Prediction of regulation of
new genes, including amino acid transporters
|
|
PS
5 U.
Ohler, G. Stemmer and H. Niemann
Principal Component Analysis of DNA structural features and its
application to human promoter finding
|
|
PS
6 K.
Patel and H.M. Cartwright
Reverse Engineering Protein Interaction Networks from Proteomics
Data
|
|
PS
7 D.
Rodionov
Transcriptional regulation of pentose utilization systems in the
Bacillus/Clostridium group of bacteria
|
|
PS
8 N.V
Oleinikova, G.A. Bogopolsky, P.K. Vlasov, Sh.R. Sunyaev, and
M.A. Roytberg
Accuracy of the pair-wise protein sequence alignment: From the
observations to a new approach
|
|
PS
9 A.
Gerasimova
Computational analysis of regulatory sites in bacterial genomes. FNR-
and ANR-binding sites
|
|
PS
10 M.
Nielsen, O. Lund, C. Lundegaard, T.N. Petersen, J. Bohr, S.
Brunak, G.P. Gippert
Automated modeling of protein structures
|
|
PS
11 T.
Gavrilova and A. Voinov
Visual Structured Analysis for Knowledge Acquisition
|
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