Probabilistic modeling of pseudorabies virus infection in a neural circuit

Siamak K. Sorooshyari, Matthew P. Taylor, H. Vincent Poor

Research output: Contribution to journalArticle

Abstract

Viral transneuronal tracing methods effectively label synaptically connected neurons in a time-dependent manner. However, the modeling of viral vectors has been largely absent. An objective of this article is to motivate and initiate a basis for computational modeling of viral labeling and the questions that can be investigated through modeling of pseudorabies virus (PRV) virion progression in a neural circuit. In particular, a mathematical model is developed for quantitative analysis of PRV infection. Probability expressions are presented to evaluate the progression of viral labeling along the neural circuit. The analysis brings forth various parameters, the numerical values of which must be attained through future experiments. This is the first computational model for PRV viral labeling of a neural circuit.

Original languageEnglish (US)
Pages (from-to)1231-1246
Number of pages16
JournalJournal of Computational Biology
Volume25
Issue number11
DOIs
StatePublished - Nov 1 2018

All Science Journal Classification (ASJC) codes

  • Modeling and Simulation
  • Molecular Biology
  • Genetics
  • Computational Mathematics
  • Computational Theory and Mathematics

Keywords

  • probabilistic modeling
  • pseudorabies virus
  • viral tracing

Fingerprint Dive into the research topics of 'Probabilistic modeling of pseudorabies virus infection in a neural circuit'. Together they form a unique fingerprint.

  • Cite this