Searching for genes and reconstructing the past: Messy solutions to good 
             problems and good solutions to messy problems

                         Junhyong Kim
             Department of Ecology and Evolutionary Biology
                        Yale University

Problems in computational biology and bioinformatics require flexible 
approaches using a variety of quantitative tools and biological 
intuition. At times the problems are well defined and we need to use 
whatever tools on hand--as inelegant as they may be, to solve the 
problem. I demonstrate an example where I use a combination of moving 
window profiles and non-parametric discriminant analysis to isolate 
olfactory receptor genes from the Drosophila genome database. Other more 
mature problems in computational biology require more sophisticated 
treatment. Estimation of evolutionary trees-- a tree-graph representation
of genealogical relationships, is a complex statistical problem. Here I 
show how the problem can be viewed as a geometry problem in a vector 
space of joint probability distributions. This geometric view gives a 
better intuitive approach to the evolutionary tree estimation problem and 
yields new theorems and algorithms.