The ARES Project: Cloud Services for Medical Genomics

This paper shows the cloud services provided by the project ARES. The network solutions have been illustrated in a companion paper in the same conference. The ARES project aims to deploy CDN services over a broadband network for accessing and exchanging genomic datasets, accessible by medical and research personnel through a Cloud interface. This paper illustrates the procedure defined to access such services, also providing a case-study simulation to show the implementation of the bioinformatics pipeline included. The experimental activity in ARES aims to gain a detailed understanding of the network problems relating to its sustainability given the increasing use of genomics for diagnostic purposes. The main aim is to allow an extensive use of genomic data through the collection of relevant information available from the network in the medical and diagnostic field diseases.

[1]  Henning Schulzrinne,et al.  Advanced caching for distributing sensor data through programmable nodes , 2013, 2013 19th IEEE Workshop on Local & Metropolitan Area Networks (LANMAN).

[2]  Wu-chun Feng,et al.  The design, implementation, and evaluation of mpiBLAST , 2003 .

[3]  Henning Schulzrinne,et al.  An enabling platform for autonomic management of the future internet , 2011, IEEE Network.

[4]  Alejandro A. Schäffer,et al.  IMPALA: matching a protein sequence against a collection of PSI-BLAST-constructed position-specific score matrices , 1999, Bioinform..

[5]  Robert D. Bjornson,et al.  TurboBLAST : a parallel implementation of blast built on the turbohub , 2002, Proceedings 16th International Parallel and Distributed Processing Symposium.

[6]  Mauro Femminella,et al.  The ARES Project: Network Architecture for Delivering and Processing Genomics Data , 2014, 2014 IEEE 3rd Symposium on Network Cloud Computing and Applications (ncca 2014).

[7]  E. Strickland The gene machine and me , 2013, IEEE Spectrum.

[8]  W. Huber,et al.  which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. MAnorm: a robust model for quantitative comparison of ChIP-Seq data sets , 2011 .

[9]  Richard Hughey,et al.  Hidden Markov models for detecting remote protein homologies , 1998, Bioinform..

[10]  E. Nunzi Uncertainties Analysis in RTT Network Measurements: the GUM and RFC Approaches , 2006, Proceedings of the 2006 IEEE International Workshop on Advanced Methods for Uncertainty Estimation in Measurement (AMUEM 2006).

[11]  W. Pearson Searching protein sequence libraries: comparison of the sensitivity and selectivity of the Smith-Waterman and FASTA algorithms. , 1991, Genomics.

[12]  L. Guarente,et al.  Molecular Biology of Aging , 1999, Cell.

[13]  M. Yandell,et al.  A beginner's guide to eukaryotic genome annotation , 2012, Nature Reviews Genetics.

[14]  Thomas R. Gingeras,et al.  STAR: ultrafast universal RNA-seq aligner , 2013, Bioinform..

[15]  Henning Schulzrinne,et al.  GIST: General Internet Signalling Transport , 2010, RFC.

[16]  David R. Kelley,et al.  Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks , 2012, Nature Protocols.

[17]  Jarek Nieplocha,et al.  ScalaBLAST: A Scalable Implementation of BLAST for High-Performance Data-Intensive Bioinformatics Analysis , 2006, IEEE Transactions on Parallel and Distributed Systems.

[18]  Nagiza F. Samatova,et al.  Efficient data access for parallel BLAST , 2005, 19th IEEE International Parallel and Distributed Processing Symposium.

[19]  S. Standard GUIDE TO THE EXPRESSION OF UNCERTAINTY IN MEASUREMENT , 2006 .

[20]  Paolo Romano,et al.  Design and Evaluation of a Parallel Invocation Protocol for Transactional Applications over the Web , 2014, IEEE Transactions on Computers.

[21]  Mark Stitt,et al.  RobiNA: a user-friendly, integrated software solution for RNA-Seq-based transcriptomics , 2012, Nucleic Acids Res..

[22]  Yongchao Liu,et al.  CUSHAW: a CUDA compatible short read aligner to large genomes based on the Burrows-Wheeler transform , 2012, Bioinform..

[23]  M S Waterman,et al.  Identification of common molecular subsequences. , 1981, Journal of molecular biology.

[24]  E. Myers,et al.  Basic local alignment search tool. , 1990, Journal of molecular biology.

[25]  Henning Schulzrinne,et al.  NSIS: a new extensible IP signaling protocol suite , 2005, IEEE Communications Magazine.

[26]  Henning Schulzrinne,et al.  Gossip-based signaling dissemination extension for next steps in signaling , 2012, 2012 IEEE Network Operations and Management Symposium.

[27]  Wu-chun Feng,et al.  Parallel genomic sequence-search on a massively parallel system , 2007, CF '07.

[28]  Sean R. Eddy,et al.  Profile hidden Markov models , 1998, Bioinform..