Transcript inria - Inra

Journées INRA - INRIA
Les sciences de la vie et de
l'environnement
dans la stratégie de l'INRIA
Mai 2007
Les sciences de la vie et de l'environnement
dans la stratégie de l'INRIA
 Introduction
 Quelques illustrations
 Principales thématiques de recherche
 Plan stratégique 2008 - 2012
Journées INRA - INRIA
2
INRIA
 Research in Computer and Information Science and Engineering
 INRIA fosters a close integration of
research - development - transfer
 It offers to associated universities and research partners
 Scientific and organizational leadership in its areas
 A vision, a strategic plan, and a research road-map
 Research facilities and support
 Strong industrial partnership for technology development &
transfer
Journées INRA - INRIA
3
INRIA
 A total work force of 3600 persons
 1100 researchers and faculty members
 1000 doctoral candidates
 1000 engineers, technicians and staff
 500 post-docs and visiting scientists
2100 INRIA employees including 500 permanent scientists
1500 partners employees
 INRIA budget of 165 M€
 Over 20% from grants and IP products
 Consolidated budget of INRIA activities : 250 M€
Journées INRA - INRIA
4
Research centers
INRIA
FUTURS,
Lille
Metz
INRIAParis
Rocquencourt
Lannion
LORIA Strasbourg
Nancy
INRIA
FUTURS
Saclay
IRISA
Rennes
Besançon
Nantes
Lyon
INRIA Rhône-Alpes
Grenoble
INRIA FUTURS
Bordeaux
Montpellier
Journées INRA - INRIA
Marseille
INRIA
Sophia Antipolis
5
Research Centers
Lille
Nancy
Rennes
Paris-Rocquencourt
Saclay
Grenoble
Bordeaux
Journées INRA - INRIA
Sophia Antipolis
6
Environment and life sciences at INRIA
Over 20 project-teams directly involved in this domains
 Helix, Symbiose, Contraintes, Bang, ABS , Vista
 Digiplants, Comore, VirtualPlants
 Clime, Moïse, Mere, Bang, Ariana
 Asclepios, Demar, Odyssee, Sysiphe, Visages, Reo
About as many groups contribute to the domain
 Apics, Coprin, Evasion, Anubis,
 Geometrica, Caiman,
 Opale, Orion, Smash,
 Omega, Tropics, Imedia, Dream
 Orpailleur, Cortex, Tao, Texmex, etc.
Journées INRA - INRIA
7
Les sciences de la vie et de l'environnement
dans la stratégie de l'INRIA
 Introduction
 Quelques illustrations
 Principales thématiques de recherche
 Plan stratégique 2008 - 2012
Journées INRA - INRIA
8
MOISE : Modélisation, Observations, Identification en
Sciences de l’Environnement
 Understanding and predicting natural processes : meteorology,
oceanography, hydrology, glaciology
 Social challenges: water resources, risk prevention and management, evolution
of the climate, territory planning,
Mathematics and calculus for the direct and inverse modeling in direct geophysics
Design and optimization of complexe systems complexes (several coupled
models, data assimilation)
Processing of heterogeneous information
Uncertainty quantification
Journées INRA - INRIA
9
Visages :Vision, Action et informations de santé
Joint team INRIA-INSERM (U746)
 Neuroimaging and modeling
 Multimodal sensors and
churgical actuators
 E-science: biomarkers,
mining, certification in
pharmacology
Journées INRA - INRIA
10
Digiplante : GreenLab3
Biomasse
Photosynthèse
n

pa ( j  i  1 )Q( j  1 )  
E ( n )Sp 
k
n

Q( n ) 
1  exp 
N a ( i ) j i



r .k 
D( j )
 e .Sp i nta 1

variation puits limbe
force de
puits
0.2
No stress
W. stress
0.15
0.1
0.05
0
1
2
3
4
5
6
7
8
9
10
11
12
age organe
Efficience de l’eau
Journées INRA - INRIA
Organogénèse
Fonction puits
11
Helix : Understanding Bacterial Stress Responses
 Bacteria have capacity to adapt to variety of environmental
stresses (lack of nutrients, heat shock, crowding)
 Bacterial stress responses are controlled by complex network of
molecular interactions
 A model of E. coli carbon starvation network using piecewiseaffine models of gene regulation has been designed
 Experimental verification by means of real-time measurements of
gene expression shows the quality of model prediction
Escherichia coli
Journées INRA - INRIA
Carbon starvation network
Gene expression measurements
12
Contraintes : cell and cyrcadien cycles
 Biochemical model: Transition system (with continuous time)
 Biological property: Temporal Logic formula
 Biological validation: Model-checking
Model
BIOCHAM
Biological properties
Boolean
Simulation
Temporal logic
Differential
Query evaluation
Constraints
Stochatisc
Reaction rule learning
Temporal
Parameter search
 Models of cell cycle: over 800 reactions, 165 genes and proteins
Parteners: Institut Curie and FP6 projects
Journées INRA - INRIA
13
Les sciences de la vie et de l'environnement
dans la stratégie de l'INRIA
 Introduction
 Quelques illustrations
 Principales thématiques de recherche
 Plan stratégique 2008 - 2012
Journées INRA - INRIA
14
Biomedical Imaging
 Constant stream of better
imaging & signal modalities
 Provide complementary
anatomical & functional info
with ever increasing spatial &
temporal resolution
 From molecular to cellular to
organ scales
 Emerging new modalities and
therapies
 Emerging Large Databases
Brain
Heart
200 microns
Bladder cells
Microvessels & leukocytes Neuro-muscular junctions
Journées INRA - INRIA
15
Privileged Role of in vivo Biomedical Imaging
 Visualize, analyze and quantify physiological processes and
pathological modifications in living systems
 Analyze and quantify genesis processes : organs, tumors,
vessels, plasticity, etc.
 Mark cellular populations and track their migration, phenotypic
modifications, differentiation, apoptosis, etc.
 Observe biological processes of synthesis, expression,
translation, apoptosis, etc.
Journées INRA - INRIA
16
Virtual Physiological Human Organs
 Build personalized virtual models of human physiological
systems (e.g. cardiac, respiratory, digestive, nervous central and
peripheral, reproductive, etc.) which can be used for
 quantitative diagnosis,
 prevention of diseases,
 therapy planning and simulation
Journées INRA - INRIA
17
Virtual Neuronal Networks
 Simulate feedforward and backward dynamically connected
sets of very large populations of spiking neurons to emulate
significant aspects of visual perception.
 Explore the use of the processing of the signals generated by
brain electrical sources to design new interactions between
humans and their artifacts.
Journées INRA - INRIA
18
Large models of Cells, Plants & Ecosystems
 Build, simulate, analyze and optimize such large models to
explain the emergence of global properties from microscopic
interactions.
Journées INRA - INRIA
19
Computational Structural Biology
 Investigate the relationship between the structure of macromolecules (DNA, RNA, Proteins) and their function.
Journées INRA - INRIA
20
Computational Physiology
 Reproduce Functional properties of
living systems at various scales
nano


ATP
micro
molecules, proteins, cells
cells, tissues, organs, systems, body, etc.

Personalization requires to choose
the right level of complexity
(observations) and a limited number
of parameters
 Model normal physiology and
physiopathology
sarcomeres
meso
fibers
macro
INRIA in silico electromechanical cardiac model
organ
Journées INRA - INRIA
21
Computational Anatomy
 Statistics on Anatom
 Build standard computational models
 Establish plausible variations around standards
 Constrain Model Personalization
 Detect abnormal Deviations
Journées INRA - INRIA
22
Biomedical Image and Signal Analysis
 New tools to extract and fuse pertinent information from
complex multimodal, multidimensional and multiscale signals
 segmentation, registration, tracking, deformation, etc.
 mining, indexing, learning, etc.
 across time, modalities, scales, individuals, populations…
 Design multi-layered advanced image processing algorithms
 Geometrical,
 Statistical
 Physical,
 Physiological
Journées INRA - INRIA
23
Data Assimilation Techniques
 Innovative methods to solve very large inverse problems
 Identification of large number of parameters from huge
quantity of measurements
 Iterative vs. variational methods
 Time constraints
Journées INRA - INRIA
24
Scientific Computing
Importance of scientific computing for direct simulation
Large scale/dimension problems
Multiscale/heterogeneous problems
Uncertainties modeling
Robustness of optimization
Computational Geometry
Computational Physics
Computational Chemistry
Computational Molecular Biology
Computational Structural Biology
Journées INRA - INRIA
25
Exploring Biological Information
 Collect, structure huge amounts of biological information
 Add semantics
 Represent and Analyze Large Biological Networks
 Model their dynamics
Journées INRA - INRIA
26
Exploit massively parallel computing
 Very large data
 Heterogeneous data
 Distributed data
 Grid computing
 Parallel computing
 Semantics grids
technologies
 Confidentiality constraints
 Semantic web
 Time constraints
 Dedicated computing
platforms
Journées INRA - INRIA
27
Les sciences de la vie et de l'environnement
dans la stratégie de l'INRIA
 Introduction
 Quelques illustrations
 Principales thématiques de recherche
 Plan stratégique 2008 - 2012
Journées INRA - INRIA
28
INRIA Strategic Plan for 2008 - 2012
Research Areas
 Algorithmic of Biology & Medicine
 Ubiquitous Information, Computation & Communication
 Interacting with Real & Virtual Worlds
 Modeling, Simulating, & Optimizing Complex Systems
 Guarantied & Secure Computing
 Computational Sciences
 Computational Engineering : Embedded Systems
Journées INRA - INRIA
29
Algorithmic of Biology and Medicine
Design and develop computational models of living systems
matching biomedical images/signals/measurements
 to better understand the living systems under study
 to better predict their natural normal or pathological evolution
 to better plan and simulate the potential effects of an interaction
 to better control them and repair their possible dysfunctions
Journées INRA - INRIA
30
Algorithmic of Biology and Medicine
Interpretation
(diagnosis)
Medical
Images
and
Signals
Geometry
Statistics
Physics
Physiology
Identification
(personalization)
Journées INRA - INRIA
Computational
Models
of
human body
Prediction of
evolution
Therapy
planning
Therapy
simulation
31
Algorithmic of Biology and Medicine
 Computational Physiology : reproduce personalized functional
properties of living systems at various scales
 Computational Anatomy: standard and abnormal models
 Biomedical Image and Signal Analysis
 Data Assimilation Techniques: very large inverse problems
 Scientific Computing : computational geometry, physics,
chemistry, molecular biology, structural biology
 Exploring biological Information
 Exploiting massively parallel computing
Journées INRA - INRIA
32
Numerical Sciences
 Digital cells
 Digital plants
 Digital ecology
 Digital biosphere and environment
 Digital material
Journées INRA - INRIA
33
Digital Cell
 Computational structural biology
 Relationship between structure and action of complex
molecular machinery
 Functional genomic, genes - protein expression and regulation
networks
 Assembly and mechanical functions of the cytoskeleton in the
cell motility and dynamic behavior
Journées INRA - INRIA
34
Digital ecology
 Heterogeneous representation, modeling and integration
 Differential models for low trophic levels
 Structured population models
 Individual-based models for higher trophic species
taking into account the geophysical environment, biotope,
interaction between species, etc.
 Integration of data from sensor networks, satellites and georeferenced images
 Prediction, visualization, conservation planning
Journées INRA - INRIA
35
Digital Environment
 Platforms and systems for
Monitoring, forecasting, risk management at local and global scales
Integrating models and data
 Measured evolution of the biosphere
 To assess the landscape modifications on earth, the diffusion of
a pollutant in a river, the plankton composition in the oceans
 To predict the future evolution of the biotope
Journées INRA - INRIA
36
Digital Environment
 Direct modeling: mathematical and numerical methods, scientific
computing, probabilistic modeling
 Forecasting error assessment: modeling uncertainty by
deterministic or stochastic methods, forecasting of extreme events
 Inverse modeling: data assimilation, optimal control, filtering
 Sensor networks
 Large-scale issues
Journées INRA - INRIA
37
Digital Environment
 Automatic image indexing, retrieval and analysis
 Data representation and processing: sensors fusion, Geographic
Information Systems, decision support systems, etc.
 3D visualization: visualization of forecast results, use of virtual
environments for what-if scenario, CAD
 Software engineering: management of complex and evolving
systems
 Grid computing: access to distributed computing and data
resources, parallel computing, real-time and security issues
Journées INRA - INRIA
38
Inria Strategic Plan
Digital
Sciences
Digital
engineering
Algorithmic of Biology & Medicine

Information, Computation & Communication
Everywhere


Interacting with Real & Virtual Worlds


Modeling, Simulating, & Optimizing Complex
Systems


Guarantied & Secure Computing
Journées INRA - INRIA

39