A novel approach for protein subcellular location prediction using amino acid exposure.

ABSTRACT:

Background

Proteins perform their functions in associated cellular locations. Therefore, the study of protein function can be facilitated by predictions of protein location. Protein location can be predicted either from the sequence of a protein alone by identification of targeting peptide sequences and motifs, or by homology to proteins of known location. A third approach, which is complementary, exploits the differences in amino acid composition of proteins associated to different cellular locations, and can be useful if motif and homology information are missing. Here we expand this approach taking into account amino acid composition at different levels of amino acid exposure.

Results

Our method has two stages. For stage one, we trained multiple Support Vector Machines (S

SUBMITTER: Mer AS 

PROVIDER: S-EPMC4219330 | biostudies-literature | 2013 Nov

REPOSITORIES: biostudies-literature