PSLIP: SVM based protein subcellular localization prediction using multiple physicochemical properties.

ABSTRACT:

Background

Protein subcellular localization is an important determinant of protein function and hence, reliable methods for prediction of localization are needed. A number of prediction algorithms have been developed based on amino acid compositions or on the N-terminal characteristics (signal peptides) of proteins. However, such approaches lead to a loss of contextual information. Moreover, where information about the physicochemical properties of amino acids has been used, the methods employed to exploit that information are less than optimal and could use the information more effectively.

Results

In this paper, we propose a new algorithm called pSLIP which uses Support Vector Machines (SVMs) in conjunction with multiple physicochemical properties of amino acids to predict

SUBMITTER: Sarda D 

PROVIDER: S-EPMC1182350 | biostudies-literature | 2005 Jun

REPOSITORIES: biostudies-literature