The analysis of antigenic data: Application to influenza.

Poster number: 0

Alan Scott Lapedes

  1. Theoretical Division Los Alamos National Laboratory, Los Alamos, NM 87545

The analysis of genetic (sequence) data underwent a revolution due to automated sequencing technologies and the creation of bioinformatics algorithms to extract useful information from sequence data. The analysis of antigenic data on the other hand, has been relatively unexplored from an algorithmic standpoint, although it is an important and abundant class of data characterizing the interaction of the immune system with pathogens. Ongoing intensive global surveillance efforts by public health agencies to monitor the evolution of influenza virus produces a wealth of both genetic and antigenic data. Recently (Science 305, p. 371 July 16 2004) we developed and applied algorithms to analyse antigenic data, and compared and contrasted the antigenic versus genetic evolution of influenza virus (subtype H3N2, the dominant circulating subtype today) over more than 30 years.

I will describe these algorithms and their applications to influenza, and the suprising and useful conclusion that the antigenic evolution of influenza occurs in a low-dimensional antigenic space.