Analytical Ultracentrifugation Data Analysis with UltraScan-III (original) (raw)

Abstract

The current status of the UltraScan-III (US3) data analysis software suite is described. An overview of the US3 concepts, software layout, the data workflows and US3 components is presented, followed by a discussion of the analysis methods and their applications. Also described are visualization modules for analysis results, US3’s utilities and simulation tools, as well as the collaboration environments for online data and result exchange.

Similar content being viewed by others

References

• Bhattacharyya SK et al (2006) Development of fast fiber based UV-vis multiwavelength detector for an ultracentrifuge. Progr Colloid Polym Sci 131:9–22
  Article CAS Google Scholar
• Brookes EH, Demeler B (2007) Parsimonious regularization using genetic algorithms applied to the analysis of analytical ultracentrifugation experiments. In: GECCO '07 proceedings of the 9th annual conference on genetic and evolutionary computation. ACM, New York, pp 361–368. ISBN: 978-1-59593-697-4. doi:10.1145/1276958.1277035
• Brookes EH, Demeler B (2008) Parallel computational techniques for the analysis of sedimentation velocity experiments in UltraScan. Colloid Polym Sci 286:138–148
  Article Google Scholar
• Brookes EH, Boppana RV, Demeler B (2006) Computing large sparse multivariate optimization problems with an application in biophysics. In: Proceedings of the SC 2006 conference. ACM/IEEE. doi:10.1109/SC.2006.18 E-ISBN: 0-7695-2700-0 Print ISBN: 0-7695-2700-0 INSPEC Accession Number: 9343095
• Brookes EH, Cao W, Demeler B (2010a) A two-dimensional spectrum analysis for sedimentation velocity experiments of mixtures with heterogeneity in molecular weight and shape. Eur Biophys J 39:405–414
  Article PubMed Google Scholar
• Brookes E, Demeler B, Rosano C, Rocco M (2010b) The implementation of SOMO (SOlution MOdeller) in the UltraScan analytical ultracentrifugation data analysis suite: enhanced capabilities allow the reliable hydrodynamic modeling of virtually any kind of biomacromolecule. Eur Biophys J 39(3):423–435
  Article CAS PubMed PubMed Central Google Scholar
• Brookes E, Demeler B, Rocco M (2010c) Developments in the US-SOMO bead modeling suite: new features in the direct residue-to-bead method, improved grid routines, and influence of accessible surface area screening. Macromol Biosci 10(7):746–753. doi:10.1002/mabi.200900474
  Article CAS PubMed Google Scholar
• Brookes E, et al (2013) US-SOMO cluster methods: year one perspective. XSEDE ’13. In: Proceedings of the conference on extreme science and engineering discovery environment: gateway to discovery, at San Diego, California 01/2013. doi:10.1145/2484762. 2484815. ISBN: 9781450321709
• Cao W, Demeler B (2005) Modeling analytical ultracentrifugation experiments with an adaptive space-time finite element solution of the Lamm equation. Biophys J 89(3):1589–1602
  Article CAS PubMed PubMed Central Google Scholar
• Cao W, Demeler B (2008) Modeling analytical ultracentrifugation experiments with an adaptive space-time finite element solution for multi-component reacting systems. Biophys J 95(1):54–65
  Article CAS PubMed PubMed Central Google Scholar
• Cölfen H et al (2010) The open AUC project. Eur Biophys J 39(3):347–359
  Article PubMed PubMed Central Google Scholar
• Demeler B (2009) High-resolution modeling of hydrodynamic experiments with UltraScan. http://www.XSEDE.org/gateways/projects.php?id=77
• Demeler B (2010) Methods for the design and analysis of sedimentation velocity and sedimentation equilibrium experiments with proteins. Curr Protoc Protein Sci 07: Unit 7.13. doi:10.1002/0471140864.ps0713s60 PMCID: PMC4547541
• Demeler B, Brookes EH (2008) Monte Carlo analysis of sedimentation experiments. Colloid Polym Sci 286:129–137
  Article CAS Google Scholar
• Demeler B, van Holde KE (2004) Sedimentation velocity analysis of highly heterogeneous systems. Anal Biochem 335:279–288
  Article CAS PubMed Google Scholar
• Demeler B et al (2010) Characterization of reversible associations by sedimentation velocity with UltraScan. Macromol Biosci 10(7):775–782. PMID: 20486142
  Article CAS PubMed Google Scholar
• Demeler B et al (2014) Characterization of size, anisotropy, and density heterogeneity of nanoparticles by sedimentation velocity. Anal Chem 86(15):7688–7695
  Article CAS PubMed PubMed Central Google Scholar
• Gorbet G et al (2014) A parametrically constrained optimization method for fitting sedimentation velocity experiments. Biophys J 106:1741–1750
  Article CAS PubMed PubMed Central Google Scholar
• Laue TM, Shah BD, Ridgeway TM, Pelletier SL (1992) Computer-aided interpretation of analytical sedimentation data for proteins. In: Harding SE, Rowe AJ, Horton JC (eds) Analytical ultracentrifugation in biochemistry and polymer science. Royal Society of Chemistry, Cambridge, pp 90–125
  Google Scholar
• Marru S, et al (2011) Apache Airavata: a framework for distributed applications and computational workflows. In: GCE ’11 Proceedings of the 2011 ACM workshop on Gateway computing environments, pp 21–28, ACM New York, NY, USA. Apache Airavata: http://airavata.apache.org/
• Memon S, et al (2013) Improvements of the UltraScan scientific gateway to enable computational jobs on large-scale and open-standards based cyberinfrastructures. In: XSEDE ’13 Proceedings of the conference on extreme science and engineering discovery environment: gateway to discovery No. 39, ACM New York, ISBN: 978-1-4503-2170-9, doi:10.1145/2484762.2484800
• Memon S, et al (2014) Advancements of the UltraScan scientific gateway for open standards-based cyberinfrastructures. Concurr Computat Pract Exper, Wiley. doi: 10.1002/cpe.3251
  Google Scholar
• Schilling K (2014) A multiwavelength capable detector for the analytical ultracentrifuge (Nanolytics, Potsdam, Germany). Personal Communication
  Google Scholar
• Schuck P, Demeler B (1999) Direct sedimentation analysis of interference optical data in analytical ultracentrifugation. Biophys J 76(4):2288–2296
  Article CAS PubMed PubMed Central Google Scholar
• Stafford WF (1992) Boundary analysis in sedimentation transport experiments: a procedure for obtaining sedimentation coefficient distributions using the time derivative of the concentration profile. Anal Biochem 203(2):295–301
  Article CAS PubMed Google Scholar
• UltraScan-III wiki: http://wiki.bcf2.uthscsa.edu/ultrascan3/

Download references

Author information

Authors and Affiliations

1. Department of Biochemistry, The University of Texas Health Science Center at San Antonio, San Antonio, TX, 78229, USA
   Borries Demeler & Gary E. Gorbet

Authors

1. Borries Demeler
2. Gary E. Gorbet

Corresponding author

Correspondence toBorries Demeler .

Editor information

Editors and Affiliations

1. Graduate School of Engineering, Osaka University, Suita, Osaka, Japan
   Susumu Uchiyama
2. Life Science Research Center, Nihon University, Fujisawa, Kanagawa, Japan
   Fumio Arisaka
3. Department of Neurology, Harvard Medical School, Boston, Massachusetts, USA
   Walter F. Stafford
4. BITC, University of New Hampshire, Durham, New Hampshire, USA
   Tom Laue

Rights and permissions

Copyright information

© 2016 Springer Japan

About this chapter

Cite this chapter

Demeler, B., Gorbet, G.E. (2016). Analytical Ultracentrifugation Data Analysis with UltraScan-III. In: Uchiyama, S., Arisaka, F., Stafford, W., Laue, T. (eds) Analytical Ultracentrifugation. Springer, Tokyo. https://doi.org/10.1007/978-4-431-55985-6\_8

Download citation

• .RIS
• .ENW
• .BIB
• DOI: https://doi.org/10.1007/978-4-431-55985-6\_8
• Published: 14 May 2016
• Publisher Name: Springer, Tokyo
• Print ISBN: 978-4-431-55983-2
• Online ISBN: 978-4-431-55985-6
• eBook Packages: Biomedical and Life SciencesBiomedical and Life Sciences (R0)

Keywords

Publish with us