AIM-BLAST-AJAX Interfaced Multisequence Blast

G Aravindhan,T.K Subazini,R Sathish Kumar,G Ramesh Kumar,K Subha,Alpana Dey,Krishna Kant

doi:10.4137/pri.s2260

Abstract

AIM-BLAST, AJAX Interfaced Multisequence Blast, is a simplified tool developed to facilitate the multiple sequences blast using AJAX as an interface. This tool has been integrated with the SOAP services of EBI NCBI Blast and the functionality of AJAX (Asynchronous Javascript and XML), so as to minimize the enormous bandwidth consumption while carrying out blast analysis for many sequences at an instance. Although a few tools for multiple sequences blast are already available online, they are restricted only to a limited number of genomes and consume several bytes of data transfer for receiving the results. Further, AIM-BLAST also has enhanced features for automated parsing of the Blast results of individual sequence and presenting them as “one sequence-one function” manner. This will save the users time and effort in interpreting the bulky blast results to identify one suitable hit. The results of the blast search in this tool are displayed in an easily interpretable table format that makes the tool user-friendly too. Hence this tool, with a laconic framework, will remain a well structured, flexible and a highly controlled Blast Program for investigating numerous sequences at a stretch with the consumption of reduced level of data transfer.

Highlights

Past decade have created enormous volumes of biological data that are deposited in the online repositories.[1]
Both the AIM-BLAST and the EBI-NCBI BLAST are run in the Firefox Web browser and the HttpFox, a Firefox add-on is operated at the backend to measure the amount of bandwidth consumption during the analysis
As per the resultant Table, it is observed that EBI-NCBI Blast consumed an overall data transfer of 12.62 Mega Bytes viz. 0.8 MB of data sent to the server and 11.80 MB of data received from the server for analyzing just 30 sample sequences

Summary

Introduction

Past decade have created enormous volumes of biological data that are deposited in the online repositories.[1] With such a largely mounted data, it has become the most vital challenge for the scientific community to investigate these raw sequences and reproduce their functions effectively. Delineating such meaningful information will facilitate a better insight into the complex biological systems. In spite of various advanced strategies for identifying the protein functions were carried out earlier, only 50%–60% of genes have been identified with known functions in most completely sequenced genomes.[2] determining the role of proteins become the most focused research areas of post-genome era. The traditional biochemical/molecular approaches can produce accurate information, they consume a lot of materials, manpower and man-hour making the process cost ineffective.[3]

Objectives

Methods

Results

Conclusion