Multiple alignment will then be particularly emphasized. Finally, we will discuss the interplay between string algorithms and algorithms for reconstructing evolutionary history, both in the form of evolutionary trees and in non-tree representations. While the field is still relatively new, a few fundamental approaches are emerging, many based on combinatorial optimization. This tutorial will survey what's known about combinatorial algorithms for DNA sequence assembly and physical mapping, and point to some of the directions of current research. Specific topics include approximation of shortest superstrings, generalization to error and reverse complementarity, local search for mapping by unique and non-unique probes, and guarantees in the presence of chimerism.
Data mining combines methods from machine learning, statistics, and databases.
Data mining has recently attracted a lot of attention from the research community and from the industrial sector. In these lectures we discuss briefly the motivation and the application areas of the research in data mining. We concentrate on the basic algorithmic problems of data mining and study how the problems and methods of data mining differ from those used in machine learning and in statistics. This tutorial will survey methods to derive phylogenetic trees from molecular sequences. Over time many fields have contributed to this problem.