RNAVLab: A virtual laboratory for studying RNA secondary structures based on grid computing technology

  • Authors:

  • Michela Taufer;Ming-Ying Leung;Thamar Solorio;Abel Licon;David Mireles;Roberto Araiza;Kyle L. Johnson

  • Affiliations:

  • Department of Computer and Information Sciences, University of Delaware, Newark, DE 19716, United States;Department of Mathematical Sciences, The University of Texas at El Paso, El Paso, TX 79968, United States and Bioinformatics Program, The University of Texas at El Paso, El Paso, TX 79968, United ...;Department of Computer Science, The University of Texas at Dallas, Richardson, TX 75080, United States;Department of Computer and Information Sciences, University of Delaware, Newark, DE 19716, United States;Department of Computer Science, The University of Texas at El Paso, El Paso, TX 79968, United States;Department of Computer Science, The University of Texas at El Paso, El Paso, TX 79968, United States;Department of Biological Sciences, The University of Texas at El Paso, El Paso, TX 79968, United States and Border Biomedical Research Center, The University of Texas at El Paso, El Paso, TX 79968 ...

  • Venue:
  • Parallel Computing
  • Year:
  • 2008

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Abstract

As ribonucleic acid (RNA) molecules play important roles in many biological processes including gene expression and regulation, their secondary structures have been the focus of many recent studies. Despite the computing power of supercomputers, computationally predicting secondary structures with thermodynamic methods is still not feasible when the RNA molecules have long nucleotide sequences and include complex motifs such as pseudoknots. This paper presents RNAVLab (RNA Virtual Laboratory), a virtual laboratory for studying RNA secondary structures including pseudoknots that allows scientists to address this challenge. Two important case studies show the versatility and functionalities of RNAVLab. The first study quantifies its capability to rebuild longer secondary structures from motifs found in systematically sampled nucleotide segments. The extensive sampling and predictions are made feasible in a short turnaround time because of the grid technology used. The second study shows how RNAVLab allows scientists to study the viral RNA genome replication mechanisms used by members of the virus family Nodaviridae.