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Title

GRIMD: distributed computing for chemists and biologists

 

Authors

Stefano Piotto1*, Luigi Di Biasi2, Simona Concilio3, Aniello Castiglione2 & Giuseppe Cattaneo2

 

Affiliation

1Department of Pharmacy, University of Salerno, Via Giovanni Paolo II, 132, 84084 Fisciano, Salerno Italy; 2Department of Computer Science, University of Salerno, Via Giovanni Paolo II, 132, 84084 Fisciano, Salerno Italy; 3Department of Industrial Engineering, University of Salerno, Via Giovanni Paolo II, 132, 84084 Fisciano, Salerno Italy

 

Email

s.piotto@gmail.com; *Corresponding author

 

Article Type

Software

Date

Received October 04, 2013; Revised November 29 2013; Accepted January 06, 2014; Published January 29, 2014

 

Abstract

Motivation: Biologists and chemists are facing problems of high computational complexity that require the use of several computers organized in clusters or in specialized grids. Examples of such problems can be found in molecular dynamics (MD), in silico screening, and genome analysis. Grid Computing and Cloud Computing are becoming prevalent mainly because of their competitive performance/cost ratio. Regrettably, the diffusion of Grid Computing is strongly limited because two main limitations: it is confined to scientists with strong Computer Science background and the analyses of the large amount of data produced can be cumbersome it. We have developed a package named GRIMD to provide an easy and flexible implementation of distributed computing for the Bioinformatics community. GRIMD is very easy to install and maintain, and it does not require any specific Computer Science skill. Moreover, permits preliminary analysis on the distributed machines to reduce the amount of data to transfer. GRIMD is very flexible because it shields the typical computational biologist from the need to write specific code for tasks such as molecular dynamics or docking calculations. Furthermore, it permits an efficient use of GPU cards whenever is possible. GRIMD calculations scale almost linearly and, therefore, permits to exploit efficiently each machine in the network. Here, we provide few examples of grid computing in computational biology (MD and docking) and bioinformatics (proteome analysis).

 

Availability

GRIMD is available for free for noncommercial research at www.yadamp.unisa.it/grimd

 

Supplementary information

www.yadamp.unisa.it/grimd/howto.aspx.

 

Citation

Piotto  et al. Bioinformation 10(1): 043-047 (2014)
 

Edited by

P Kangueane

 

ISSN

0973-2063

 

Publisher

Biomedical Informatics

 

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.