Population Modeling Working Group
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Contents |
Population Modeling Working Group
Working Group co-leads: Madhav Marathe and TBD
Goals and Objectives:
One of the fundamental challenges of multiscale modeling is to provide insights into collective processes and phenomena emerging in populations of individuals (or individual components) from their basic characteristics and interactions. Put more simply, it is the problem of scaling behavior from one to many, to identify relevant summary statistics and the order parameters that operate on higher scales. While our focus is mainly on human populations, the mathematical, statistical and computational issues that arise in predicting population-level properties (e.g., population dynamics, growth, extinction, migration etc) also arise in populations of molecules, bacteria, viruses, organelles, cells, and tissues. The primary goal of this WG is to survey the field of population modeling across multiple scales, introduce basic population concepts used in statistics, genetics and survival analysis, and to provide links to resources and available software. The WG invites discussion of examples, case studies and important papers in the field. It is meant to be and open and evolving forum.
Participants:
Funding Opportunities:
R13 to foster/build interdisciplinary research teams: http://grants.nih.gov/grants/guide/pa-files/PA-10-106.html
PAR-11-203 Interagency U01 on Predictive Multiscale Models for Biomedical, Biological, Behavioral, Environmental and Clinical Research: http://grants.nih.gov/grants/guide/pa-files/PAR-11-203.html
Current State of the Art:
Challenges and Opportunities:
Disease Modeling:
- Cancer:
- Scales: genomic, cell-level, tissue-level, population-level
- Targets:
- a) temporal patterns: incidence, survival, mortality
- b) spatial patterns: geographic/ethnic and socioeconomic factors, risk factors, ...
- c) impact of screening and interventions
- Data:
- a) genomic (transcriptome, genome, metabolome, proteome, ...)
- b) genetic model systems (e.g. murine), chemical carcinogenesis, animal studies, ...
- c) cohort data, case-control data
- d) registry data (e.g. SEER)
- Methods/Models & Approaches:
(fill in)
- Infectious Diseases
- Scales:
- Targets:
- Data:
- Methods/Models & Approaches:
- Other (e.g. economic development, ethnic conflict, war, ...)
Journal Articles:
Presentations:
TO BE RESCHEDULED
Chris Barrett will bring a fresh, broad perspective to issues related to scaling simulations to large populations, incorporating population heterogeneity, and especially an analysis of validation and the role of prediction.
