Abstract
The amino acid sequence of a protein is the key to understanding its structure and ultimately its function in the cell. This paper addresses the fundamental issue of encoding amino acids in ways that the visualization of protein sequences facilitates the decoding of its information content. We show that a feature-based representation in a three-dimensional (3D) space derived from substitution matrices provides an adequate representation from which the domain content of a protein can be predicted. In addition, we show that each dimension of the feature space can be related to a physical property of the amino acids.
Index
Terms
Available to subscribers and IEEE members.
References
Available to subscribers and IEEE members.
Citing Documents
Available to subscribers and IEEE members.
Cart
