Toward Protein Structure Analysis with Self-Organizing Maps

- Establishing structure-function relationships on the proteomic scale is a unique challenge faced by bioinformatics and molecular biosciences. Large protein families represent natural libraries of analogues of a given catalytic or protein function, thus making them ideal targets for the investigation of structure-function relationships in proteins. To this end, we have developed a new technique for analyzing large amounts of detailed molecular structure information focusing on the functional centers of homologous proteins. Our approach uses unsupervised machine learning, in particular, selforganizing maps. The information captured by a selforganizing map and stored in its reference models highlights the essential structure of the proteins under investigation and can be effectively used to study detailed structural differences and similarities among homologous proteins. Our preliminary results obtained with a prototype based on these techniques demonstrate that we can classify proteins...

• Type: Conference
• Year: 2005
• Where: CIBCB
• Authors: Lutz Hamel, Gongqin Sun, Jing Zhang
• Keywords: CIBCB 2005, Homologous Proteins, Protein, Structure-function Relationships