NFU-Enabled FASTA: moving bioinformatics applications onto wide area networks

Area of Science:

• Computational Biology
• Bioinformatics
• Network Science

Background:

• Internet technologies enable distributed research collaborations beyond traditional lab settings.
• Existing technologies lack integrated data storage and computation as a shared network resource.
• The Internet Backplane Protocol (IBP) offers a framework for computation-enabled logistical networking.

Purpose of the Study:

• To demonstrate software distributing the FASTA algorithm and datasets over a wide area network.
• To assess the efficiency of computation-enabled logistical networks for large-scale bioinformatics tasks.
• To evaluate the adaptability of genome-scale data storage within logistical networks.

Main Methods:

• Implementation of software utilizing IBP's computation-enabled logistical networking components.
• Distribution of the FASTA algorithm and relevant datasets across a wide area network.
• Testing performance with large datasets and genome-scale data storage.

Main Results:

• Computation-enabled logistical networks significantly reduce FASTA algorithm running time compared to local or non-distributed methods.
• Genome-scale datasets are adaptable to logistical network storage.
• The approach effectively distributes FASTA computation over large, network-stored datasets.

Conclusions:

• IBP-enabled networks efficiently distribute FASTA computation for large datasets.
• This method provides distributed collaborators access to shared storage for massive life science data.
• The framework offloads computation from clients to the network, simplifying resource access.