Using open-source software technologies and standardized data structures to build advanced applications for high-throughput experimentation environments

Review of Scientific Instruments

Volumn 76, Issue 6, 2005, Pages

  Zech, Torsten ^a   Sundermann, Andreas ^a   Födisch, Ringo ^a   Saupe, Michael ^a  

^a Hte Aktiengesellschaft ^*  (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

DATA MANAGEMENT; HIGH-THROUGHPUT EXPERIMENTATION (HTE); HIGH-THROUGHPUT MATERIALS; OPEN-SOURCE SOFTWARE;

AUTOMATION; COMPUTER SOFTWARE; DATA PROCESSING; DATA REDUCTION; DATA STRUCTURES; DATABASE SYSTEMS; INTERCONNECTION NETWORKS; PARAMETER ESTIMATION; STANDARDIZATION; XML;

THROUGHPUT;

EID: 20644441326     PISSN: 00346748     EISSN: None     Source Type: Journal    
DOI: 10.1063/1.1906104     Document Type: Article

References (34)

1. J. N. Cawse, Experimental Design for Combinatorial and High Throughput Materials Development (Wiley, New York, 2003).
2. L. Bonetta, Nat. Methods 1, 169 (2004).
3. A. Gobbi, S. Funeriu, J. Ioannou, J. Wang, M.-L. Lee, C. Palmer, B. Bamford, and R. Hewitt, J. Chem. Inf. Comput. Sci. 44, 964 (2004).
4. A. Wilke, J. Biotechnol. 106, 147 (2003).
5. M. Dondrup, J. Biotechnol. 106, 135 (2003).
6. http://www.ec-combicat.org/
7. D. Farrusseng and C. Mirodatos, in High-Throughput Screening in Chemical Catalysis, edited by, A. Hagemeyer, P. Strasser, and, A. F. Volpe, Jr., (Wiley-VCH, Weinheim, 2004), pp. 239-270.
8. D. Farrusseng, L. Baumes, and C. Mirodatos, in High-throughput Analysis-A Tool for Combinatorial Materials Science, edited by, E. Amis, and, R. Potyrailo, (Kluwer Academic/Plenum, New York, 2003), pp. 551-580.
9. T. Zech, J. Klein, S. A. Schunk, T. Johann, F. Schüth, S. Kleditzsch, and O. Deutschmann, in High-throughput Analysis-A Tool for Combinatorial Materials Science, edited by, E. Amis, and, R. Potyrailo, (Kluwer Academic/Plenum, New York, 2003), pp. 491-523.
10. J. Klein, T. Zech, and S. A. Schunk, Appl. Catal., A 254, 121 (2003).
11. K. P. Peil, D. R. Neithamer, D. W. Patrick, B. E. Wilson, and C. J. Tucker, Macromol. Rapid Commun. 25, 119 (2004).
12. P. D. Higginson and N. W. Sach, Org. Process Res. Dev. 8, 1009 (2004).
13. http://www.kernel.org/
14. http://www.debian.org/
15. http://httpd.apache.org/
16. http://www.perl.org/
17. E. S. Raymond, The Art of UNIX Programming (Addison-Wesley Professional, Boston, 2003).
18. http://www.mged.org/
19. T. Zech, " Standards and modularity: XML-based data management and web-oriented data analysis for high throughput experimentation platforms., " Gordon Research Conference, Santa Barbara, 2004.
20. http://www.w3.org/
21. P. Murray-Rust, H. S. Rzepa, M. Wright, and S. Zara, Chem. Commun. (Cambridge) 2000, 1471.
22. http://www.w3.org/2000/xp/group/
23. J. D. Tisdall, Mastering Perl for Bioinformatics (O'Reilly, Sebastopol, 2003).
24. C. Klanner, D. Farrusseng, L. Baumes, C. Mirodatos, and F. Schüth, QSAR Comb. Sci. 22, 729 (2003).
25. R. A. Becker, W. S. Cleveland, and M. J. Shyu, J. Comput. Graph. Stat. 5, 123 (1996).
26. W. Cleveland and M. Fuentes, Trellis display: Modeling data from designed experiments., http://citeseer.ist.psu.edu/72063.html, 1997.
27. L. Kaufman and P. J. Rousseeuw, Finding Groups in Data: An Introduction to Cluster Analysis (Wiley, New York, 1990).
28. C. M. Bishop, Neural Networks for Pattern Recognition (Oxford University Press, Oxford, 1996).
29. http://www.cs.waikato.ac.nz/~ml/weka/index.html
30. http://eric.univ-lyon2.fr/~ricco/tanagra/en/tanagra.html
31. R. Ihaka and R. Gentleman, J. Comput. Graph. Stat. 5, 299 (1996).
32. http://www.r-project.org/
33. R. C. Gentleman, Genome Biology 5, R80 (2004).
34. P.-A. W. Weiss, C. Thome, and W. F. Maier, J. Comb. Chem. 6, 520 (2004).