Team, Visitors, External Collaborators
Overall Objectives
Research Program
Application Domains
Highlights of the Year
New Software and Platforms
New Results
Bilateral Contracts and Grants with Industry
Partnerships and Cooperations
Dissemination
Bibliography
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2018 Project-Team Activity Report
XPOP
Statistical modelling for life sciences
Research centre: Saclay - Île-de-France
In partnership with: Ecole Polytechnique
In collaboration with: Centre de Mathématiques Appliquées (CMAP)

Field: Digital Health, Biology and Earth
Theme: Modeling and Control for Life Sciences
Keywords:
Computer Science and Digital Science:
  • A3.1.1. - Modeling, representation
  • A3.2.3. - Inference
  • A3.3. - Data and knowledge analysis
  • A3.3.1. - On-line analytical processing
  • A3.3.2. - Data mining
  • A3.3.3. - Big data analysis
  • A3.4.1. - Supervised learning
  • A3.4.2. - Unsupervised learning
  • A3.4.4. - Optimization and learning
  • A3.4.5. - Bayesian methods
  • A3.4.6. - Neural networks
  • A3.4.7. - Kernel methods
  • A3.4.8. - Deep learning
  • A5.9.2. - Estimation, modeling
  • A6.1.1. - Continuous Modeling (PDE, ODE)
  • A6.2.2. - Numerical probability
  • A6.2.3. - Probabilistic methods
  • A6.2.4. - Statistical methods
  • A6.3.3. - Data processing
  • A6.3.5. - Uncertainty Quantification
Other Research Topics and Application Domains:
  • B1.1.4. - Genetics and genomics
  • B1.1.7. - Bioinformatics
  • B1.1.10. - Systems and synthetic biology
  • B2.2.3. - Cancer
  • B2.2.4. - Infectious diseases, Virology
  • B2.4.1. - Pharmaco kinetics and dynamics
  • B9.1.1. - E-learning, MOOC