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David Welch
Study systems include
Networks
Rapidly evolving viruses (FIV, HIV)
Selected publications
Toni T, Welch D, Strelkowa N, Ipsen A & Stumpf MP (2008). Approximate Bayesian Computation scheme for parameter inference and model selection in dynamical systems. Journal of the Royal Society Interface. In press.
Geoff Nicholls, David Welch, (2007), TraitLab: Software for fitting tree-like binary trait data. Software and manual available online
Welch D, Nicholls G, Rodrigo A, & Solomon W (2005). Integrating genealogy and epidemiology: The ancestral infection and selection graph as a model for reconstructing host virus histories. Theoretical Population Biology. 68: 65-75.
Atkinson Q, Nicholls G, Welch D & Gray R (2005). From Words to Dates: Water Into Wine, Mathemagic or Phylogenetic Inference?. Quantitative Methods in Language Comparison. Special issue of Transactions of the Philological Society, McMahon, A. (Ed) 103.2
Postdoctoral Researcher
Email: jdw21@stat.psu.edu
Phone: 814-865-1030
Office: 510 Mueller Laboratory
Research interests
I am a statistician working on methods for estimating networks using genetic and social data. The work is aimed at understanding:
- The spread of disease
- The structure of populations in which disease spreads
The networks I am interested in are defined by the mode of transmission of a disease. The nodes of the network are typically the individuals in the host population. The edges between nodes represent some type of infectious contact or path along which the disease is transmitted. For example, in vertically transmitted or inherited diseases, the edges may represent parent-child relationships; in horizontally transmitted diseases, they may represent blood transfer.
Working with others in CIDD, I am:
- Developing stochastic models for these networks
- Estimating model parameters using different types of data
- We estimate model parameters using stochastic simulation tools such as Markov chain Monte Carlo (MCMC) and approximate Bayesian computation (ABC). Developing these tools is a major part of my research.
