TITLE:
Prot-Class: A bioinformatics tool for protein classification based on amino acid signatures
AUTHORS:
Jens Lichtenberg, Brian D. Keppler, Thomas Conley, Dazhang Gu, Paul Burns, Lonnie R. Welch, Allan M. Showalter
KEYWORDS:
Bioinformatics; Protein Classification; Arabidopsis
JOURNAL NAME:
Natural Science,
Vol.4 No.12A,
December
31,
2012
ABSTRACT: Knowledge about
characteristics shared across known members of a protein family enables their
identification within the complete set of proteins in an organism. Shared
features are usually expressed through motifs, which can incorporate specific
patterns and even amino acid (AA) biases. Based on a set of classification
patterns and biases it can be determined which additional proteins may belong
to a specific family and share its functionality. A bioinformatics tool
(Prot-Class) was implemented to examine protein sequences and characterize them
based upon user-defined AA composition percentages and user defined AA
patterns. In addition the tool allows for the identification of repeated AA
patterns, biased AA compositions within windows of user-defined length, and the
characteristics of putative signal peptides and glycosylphosphatidylinositol
(GPI) lipid anchors. ProtClass is general purpose and can be applied to analyze
protein sequences from any organism. The Prot-Class source code is available
through the GNU General Public License v3 and can be accessed via the Google
Code Repository: http://code.google.com/p/prot-class/.