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Creating chemo- and bioinformatics workflows, further developments within the CDK-Taverna Project

The CDK-Taverna project aims at building an open-source pipelining solution through combination of different open-source projects such as Taverna [1] the Chemistry Development Kit (CDK) [2] and Bioclipse [3].

Pipelining or workflow tools allow for the Lego™-like, graphical assembly of I/O modules and algorithms into a complex workflow which can be easily deployed, modified and tested without the hassle of implementing it into a monolithic application. Current developments in CDK-Taverna focus on a soft computing framework which allows a flexible use of different methods from, for example, the WEKA [4] library. Additionally an implementation of the ART2a [5] algorithm is added as worker and could be used for cluster purposes. Worker which analyse and compare the cluster results are also implemented. Pgchem::Tigress [6] a chemoinformatic cartridge for a PostgresSQL database is used to allow the handling of large datasets. Therefore a number of worker for adding, selection and searching molecules from and on the database are added.

References

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    Oinn T, Addis M, Ferris M, Marvin D, Senger M, Greenwood M, Carver T, Glover K, Pocock M, Wipat A, Li P: Taverna: A tool for the composition and enactment of bioinformatics workflows. Bioinformatics. 2004, 20 (17): 3045-3054. 10.1093/bioinformatics/bth361.

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    Steinbeck C, Han YQ, Kuhn S, Horlacher O, Luttmann E, Willighagen E: The Chemistry Development Kit (CDK): An open-source Java library for chemo- and bioinformatics. J Chem Inf Comput Sci. 2003, 43: 493-500.

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    Spjuth O, Helmus T, Willighagen EL, Kuhn S, Eklund M, et al: Bioclipse: An open rich client workbench for chemo-and bioinformatics.

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    Witten IH, Frank E: Data Mining: Practical machine learning tools and techniques. 2005, Morgen Kaufmann, San Francisco, 2

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    Carpenter GA, Grossberg S, Rosen DB: Neural Networks. 1991, 4: 493-10.1016/0893-6080(91)90045-7.

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    Schmid EG: [http://pgfoundry.org/projects/pgchem/]

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Correspondence to T Kuhn.

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Keywords

  • Large Dataset
  • Cluster Result
  • Soft Computing
  • Chemistry Development
  • Current Development