SLocP Tool Box-An Integrated Platform for Predicting Sub Cellular Localization of Proteins

摘要

Prediction of subcellular location of a protein remains a challenging task in the field of computational biology. Several approaches, employing amino acid composition, Gene Ontology based, Evolutionary profile based, statistical techniques, and machine learning techniques, are adopted for predicting the exact location of the protein. Although, several approaches exist, there remains the problem in accurate prediction of the sub-localized protein. Moreover, to achieve this task, it has become mandatory to compare the results obtained by different approaches and analyze them manually, which has become a tedious job to perform. Hence, to overcome these difficulties, it is proposed to attempt in collating the available online subcellular localization prediction tools under a single platform to achieve the results with certainty. Thus, the SLocP tool box was developed, using PERL, that provides the user to submit the sequence either singly or in multiples, enabling for easy and quick comparison of results from various prediction server. Perhaps, this tool can be executable under both Linux and Windows platform.