Author(s): Matthew O. Ward, Computer Science Department, and David S. Adams, Department of Biology and Biotechnology, Worcester Polytechnic Institute, Worcester, MA 01609

Source: First IEEE Conference on Visualization in Biomedical Computing, 1990.

Abstract: This paper presents a new application area for visualization, namely nucleotide sequence analysis, and a new visualization technique, termed s correlation image (CI). The CI produced by the comparison of two sequences contains information regarding all possible alignments of the two sequences, and information of significant interest to molecular biologists (homologies) manifests itself as geometric patterns in the image. We will show the derivation and interpretation of CIs, compare them with some existing nucleotide sequence analysis techniques, and illustrate the power of CIs in uncovering previously unreported homologies.