Title: Some statistical problems in gene finding and gene mapping
 

Today, to locate all the genes in the human chromosomes and find their functions is a challenge problem to many scientists. There are two common ways to do it. One is on the prediction of gene location and gene products from experimentally uncharacterized DNA sequences, i.e., gene finding. Gene finding is a hot problem in computational biology. Another is on gene mapping that depends on a biological phenomenon, recombination, which is exploited for the purpose of determining the genetic distance between two loci. There are several statistical approaches to gene mapping such as linkage analysis, disequilibrium mapping, and microarray expression analysis etc. In this talk, we will review some statistical models and related statistical problems in gene finding and in gene mapping. We will focus on hidden Markov models and interpolated Markov models in gene finding, and Markov process models in an affected sib-pair linkage analysis.  Some of our findings on an affected sib-pair linkage analysis will also be presented.