Cloud MapReduce for Monte Carlo bootstrap applied to Metabolic Flux Analysis

Future Generation Computer Systems

Volumn 29, Issue 2, 2013, Pages 582-590

  Dalman, Tolga ^a   Dörnemann, Tim ^b   Juhnke, Ernst ^b   Weitzel, Michael ^a   Wiechert, Wolfgang ^a   Nöh, Katharina ^a   Freisleben, Bernd ^b  

^a FORSCHUNGSZENTRUM JÜLICH   (Germany)

^b PHILIPPS UNIVERSITY MARBURG   (Germany)

Author keywords

Cloud computing; Hadoop; MapReduce; Metabolic Flux Analysis; Monte Carlo bootstrap; Scientific workflows

Indexed keywords

HADOOP; MAP-REDUCE; METABOLIC FLUX ANALYSIS; MONTE CARLO; SCIENTIFIC WORKFLOWS;

CLOUD COMPUTING; DISTRIBUTED COMPUTER SYSTEMS; ENTERPRISE RESOURCE MANAGEMENT; METABOLISM; MONTE CARLO METHODS;

INTERNET;

EID: 84870237261     PISSN: 0167739X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.future.2011.10.007     Document Type: Conference Paper

References (35)

1. 13 C metabolic flux analysis Metabolic Engineering 3 3 2001 195 206
2. I.J. Taylor, E. Deelman, D.B. Gannon, and M. Shields Workflows for e-Science: Scientific Workflows for Grids 2006 Springer-Verlag New York, Inc. Secaucus, NJ, USA
3. T. Dalman, P. Droste, M. Weitzel, W. Wiechert, and K. Nöh Workflows for metabolic flux analysis: data integration and human interaction Leveraging Applications of Formal Methods, Verification, and Validation LNCS vol. 6415 2010 261 275
4. J. Dean, and S. Ghemawat MapReduce: simplified data processing on large clusters OSDI'04: Proceedings of the 6th Conference on Symposium on Operating Systems Design & Implementation 2004 USENIX Association Berkeley, CA, USA 107 113
5. T. White Hadoop: The Definitive Guide 1st ed. 2009 O'Reilly Media
6. S. Matthews, and T. Williams MrsRF: an efficient mapreduce algorithm for analyzing large collections of evolutionary trees BMC Bioinformatics 11 Suppl. 1 2010 S15
7. A. Matsunaga, M. Tsugawa, and J. Fortes CloudBLAST: combining mapreduce and virtualization on distributed resources for bioinformatics applications ESCIENCE'08: Proceedings of the 2008 4th IEEE International Conference on eScience 2008 IEEE Computer Society Washington, DC, USA 222 229
8. D.P. Wall, P. Kudtarkar, V.A. Fusaro, R. Pivovarov, P. Patil, and P.J. Tonellato Cloud computing for comparative genomics BMC Bioinformatics 11 1 2010 259 270
9. Amazon Web Services LLC, Amazon ElasticMapReduce website. http://aws.amazon.com/elasticmapreduce/ (last accessed: February 2011).
10. B. Efron, and R. Tibshirani An Introduction to the Bootstrap 1st ed. 1994 Chapman & Hall, CRC
11. 13 C metabolic flux analysis, in: Proceedings of 7th EUROSIM Congress on Modelling and Simulation, 2010.
12. T. Dalman, T. Dörnemann, E. Juhnke, M. Weitzel, M. Smith, W. Wiechert, K. Nöh, B. Freisleben, Metabolic flux analysis in the cloud, in: IEEE International Conference on eScience, 2010, pp. 57-64.
13. 13 C isotopic labeling Mass Spectrometry Reviews 28 2 2009 362 375
14. M. Weitzel, High performance algorithms for metabolic flux analysis, Ph.D. Thesis, University of Siegen, Germany, 2009.
15. 13 C metabolic flux analysis Metabolic Engineering 3 3 2001 265 283
16. W. Wiechert, and M. Wurzel Metabolic isotopomer labeling systems. Part I: global dynamic behaviour Mathematical Biosciences 169 2 2001 173 205
17. T. Andrews, F. Curbera, H. Dholakia, Y. Goland, J. Klein, F. Leymann, K. Liu, D. Roller, D. Smith, S. Thatte, I. Trickovic, S. Weerawarana, Business process execution language for web services version 1.1, May 2003.
18. T. Dörnemann, T. Friese, S. Herdt, E. Juhnke, B. Freisleben, Grid workflow modelling using grid-specific BPEL extensions, in: Proceedings of German e-Science Conference 2007, 2007, pp. 1-9.
19. T. Dörnemann, M. Smith, and B. Freisleben Composition and execution of secure workflows in WSRF-grids Proceedings of the 8th IEEE International Symposium on Cluster Computing and the Grid CCGrid'08 2008 IEEE Press 122 129
20. T. Dörnemann, E. Juhnke, and B. Freisleben On-demand resource provisioning for BPEL workflows using amazon's elastic compute cloud Proceedings of the 9th IEEE/ACM International Symposium on Cluster Computing and the Grid CCGrid'09 2009 IEEE Press 140 147
21. J. Reichwald, T. Dörnemann, T. Barth, M. Grauer, and B. Freisleben Model-driven process development incorporating human tasks in service-oriented grid environments Multikonferenz Wirtschaftsinformatik 2008 Springer-Verlag 79 90
22. W.H. Press, S.A. Teukolsky, W.T. Vetterling, and B.P. Flannery Numerical Recipes: The Art of Scientific Computing 3rd ed. 2007 Cambridge University Press
23. M.R. Chernick Bootstrap Methods: A Guide for Practitioners and Researchers 2nd ed. 2007 Wiley-Interscience
24. Hadoop wiki. http://wiki.apache.org/hadoop/HowManyMapsAndReduces (last accessed: February 2011).
25. M. Zaharia, A. Konwinski, A.D. Joseph, R.H. Katz, and I. Stoica Improving MapReduce performance in heterogeneous environments R. Draves, R. van Renesse, OSDI 2008 USENIX Association 29 42
26. H. Lin, X. Ma, J.S. Archuleta, W. Chun Feng, M.K. Gardner, Z. Zhang, Moon: mapreduce on opportunistic environments, in: IEEE International Symposium on High Performance Distributed Computing, 2010, pp. 95-106.
27. S. Ibrahim, H. Jin, L. Lu, S. Wu, B. He, and L. Qi Leen: locality/fairness-aware key partitioning for mapreduce in the cloud CloudCom 2010 IEEE 17 24
28. D. Jiang, B.C. Ooi, L. Shi, and S. Wu The performance of mapreduce: an in-depth study Proceedings of the VLDB Endowment 3 2010 472 483
29. P.-C. Chen, Y.-L. Su, J.-B. Chang, and C.-K. Shieh Variable-sized map and locality-aware reduce on public-resource grids Future Generation Computer Systems 27 6 2011 843 849
30. S. Sehgal, M. Erdelyi, A. Merzky, and S. Jha Understanding application-level interoperability: scaling-out MapReduce over high-performance grids and clouds Future Generation Computer Systems 27 5 2011 590 599
31. J. Talbot, R.M. Yoo, and C. Kozyrakis Phoenix ++: modular mapreduce for shared-memory systems Proceedings of the Second International Workshop on MapReduce and its Applications MapReduce'11 2011 ACM New York, NY, USA 9 16
32. M. Antoniewicz, J. Kelleher, and G. Stephanopoulos Determination of confidence intervals of metabolic fluxes estimated from stable isotope measurements Metabolic Engineering 2006 324 337
33. 13 C -tracer technology, Ph.D. Thesis, University of Düsseldorf, Institut für Biotechnologie, Berichte des Forschungszentrums Jülich, 3875, 2001 (in German).
34. M.R. Palankar, A. Iamnitchi, M. Ripeanu, and S. Garfinkel Amazon s3 for science grids: a viable solution? DADC'08: Proceedings of the 2008 International Workshop on Data-Aware Distributed Computing 2008 ACM 55 64
35. S.N. Srirama, P. Jakovits, and E. Vainikko Adapting scientific computing problems to clouds using MapReduce Future Generation Computer Systems 28 1 2012 184 192