Frequent-subsequence-based prediction of outer membrane proteins

A number of medically important disease-causing bacteria (collectively called Gram-negative bacteria) are noted for the extra "outer" membrane that surrounds their cell. Proteins resident in this membrane (outer membrane proteins, or OMPs) are of primary research interest for antibiotic and vaccine drug design as they are on the surface of the bacteria and so are the most accessible targets to develop new drugs against. With the development of genome sequencing technology and bioinformatics, biologists can now deduce all the proteins that are likely produced in a given bacteria and have attempted to classify where proteins are located in a bacterial cell. However such protein localization programs are currently least accurate when predicting OMPs, and so there is a current need for the development of a better OMP classifier. Data mining research suggests that the use of frequent patterns has good performance in aiding the development of accurate and efficient classification ...

• Type: Conference
• Year: 2003
• Where: KDD
• Authors: Rong She, Fei Chen 0002, Ke Wang, Martin Ester, Jennifer L. Gardy, Fiona S. L. Brinkman
• Keywords: Data Mining, Gramnegative Bacterial Proteins, Important Disease-causing Bacteria, KDD 2003, Outer Membrane Proteins