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

Abstract Background Advances in Internet technologies have allowed life science researchers to reach beyond the lab-centric research paradigm to create distributed collaborations. Of the existing technologies that support distributed collaborations, there are currently none that simultaneously support data storage and computation as a shared network resource, enabling computational burden to be wholly removed from participating clients. Software using computation-enable logistical networking components of the Internet Backplane Protocol provides a suitable means to accomplish these tasks. Here, we demonstrate software that enables this approach by distributing both the FASTA algorithm and appropriate data sets within the framework of a wide area network. Results For large datasets, computation-enabled logistical networks provide a significant reduction in FASTA algorithm running time over local and non-distributed logistical networking frameworks. We also find that genome-scale sizes of the stored data are easily adaptable to logistical networks. Conclusion Network function unit-enabled Internet Backplane Protocol effectively distributes FASTA algorithm computation over large data sets stored within the scaleable network. In situations where computation is subject to parallel solution over very large data sets, this approach provides a means to allow distributed collaborators access to a shared storage resource capable of storing the large volumes of data equated with modern life science. In addition, it provides a computation framework that removes the burden of computation from the client and places it within the network

NFU-Enabled FASTA: moving bioinformatics applications onto wide area networks-3

<p><b>Copyright information:</b></p><p>Taken from "NFU-Enabled FASTA: moving bioinformatics applications onto wide area networks"</p><p>http://www.scfbm.org/content/2/1/8</p><p>Source Code for Biology and Medicine 2007;2():8-8.</p><p>Published online 26 Nov 2007</p><p>PMCID:PMC2211279.</p><p></p>into remote FASTA application. Briefly, a shared FASTA library file is created by stripping out the FASTA algorithm and histogram creation portions from the FASTA package and converting them to a static shared library. Since the NFU computation service enabled on the IBP depots is implemented in the C programming language, the transformation of FASTA code to shared library files is also implemented in C

NFU-Enabled FASTA: moving bioinformatics applications onto wide area networks-7

<p><b>Copyright information:</b></p><p>Taken from "NFU-Enabled FASTA: moving bioinformatics applications onto wide area networks"</p><p>http://www.scfbm.org/content/2/1/8</p><p>Source Code for Biology and Medicine 2007;2():8-8.</p><p>Published online 26 Nov 2007</p><p>PMCID:PMC2211279.</p><p></p>into remote FASTA application. Briefly, a shared FASTA library file is created by stripping out the FASTA algorithm and histogram creation portions from the FASTA package and converting them to a static shared library. Since the NFU computation service enabled on the IBP depots is implemented in the C programming language, the transformation of FASTA code to shared library files is also implemented in C

NFU-Enabled FASTA: moving bioinformatics applications onto wide area networks-6

<p><b>Copyright information:</b></p><p>Taken from "NFU-Enabled FASTA: moving bioinformatics applications onto wide area networks"</p><p>http://www.scfbm.org/content/2/1/8</p><p>Source Code for Biology and Medicine 2007;2():8-8.</p><p>Published online 26 Nov 2007</p><p>PMCID:PMC2211279.</p><p></p>a database. The chunk is replicated and fragmented depending on the parameters given to the upload tool before being stored in the IBP network as IBP allocations. (B) The DBList maintains a list of all the databases that have been uploaded and are available, and the information associated with them (e.g., the no of chunks, the list of xnd files, etc)

NFU-Enabled FASTA: moving bioinformatics applications onto wide area networks-4

<p><b>Copyright information:</b></p><p>Taken from "NFU-Enabled FASTA: moving bioinformatics applications onto wide area networks"</p><p>http://www.scfbm.org/content/2/1/8</p><p>Source Code for Biology and Medicine 2007;2():8-8.</p><p>Published online 26 Nov 2007</p><p>PMCID:PMC2211279.</p><p></p>handled by the server using the LoRS upload tool and associated XND files to catalog distributed database location and replicate. Following a request for execution, the server retrieves the query file from the client and uploads the query file and modified FASTA executable onto NFU-enabled storage depots where the appropriate database chunks reside. The FASTA results are download directly from the network, modified if necessary, and returned to the client

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

<p>Abstract</p> <p>Background</p> <p>Advances in Internet technologies have allowed life science researchers to reach beyond the lab-centric research paradigm to create distributed collaborations. Of the existing technologies that support distributed collaborations, there are currently none that simultaneously support data storage and computation as a shared network resource, enabling computational burden to be wholly removed from participating clients. Software using computation-enable logistical networking components of the Internet Backplane Protocol provides a suitable means to accomplish these tasks. Here, we demonstrate software that enables this approach by distributing both the FASTA algorithm and appropriate data sets within the framework of a wide area network.</p> <p>Results</p> <p>For large datasets, computation-enabled logistical networks provide a significant reduction in FASTA algorithm running time over local and non-distributed logistical networking frameworks. We also find that genome-scale sizes of the stored data are easily adaptable to logistical networks.</p> <p>Conclusion</p> <p>Network function unit-enabled Internet Backplane Protocol effectively distributes FASTA algorithm computation over large data sets stored within the scaleable network. In situations where computation is subject to parallel solution over very large data sets, this approach provides a means to allow distributed collaborators access to a shared storage resource capable of storing the large volumes of data equated with modern life science. In addition, it provides a computation framework that removes the burden of computation from the client and places it within the network.</p