Skip to main content
Download PDF

Volume 3 Supplement 1

4th German Conference on Chemoinformatics: 22. CIC-Workshop

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

Chemistry Central Journal volume 3, Article number: P42 (2009) Cite this article

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

  1. 1.

    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.

    CAS  Article  Google Scholar 

  2. 2.

    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.

    CAS  Article  Google Scholar 

  3. 3.

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

  4. 4.

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

    Google Scholar 

  5. 5.

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

    Article  Google Scholar 

  6. 6.

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

Download references

Author information

Affiliations

  1. Cologne University Bioinformatics Center (CUBIC), Cologne, Germany

    T Kuhn

  2. University of Applied Sciences of Gelsenkirchen, Institute for Bioinformatics and Chemoinformatics, Recklinghausen, Germany

    T Kuhn & A Zielesny

  3. European Bioinformatics Institute (EBI), Cambridge, UK

    C Steinbeck

Authors
  1. T Kuhn
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. A Zielesny
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. C Steinbeck
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to T Kuhn.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reprints and Permissions

About this article

Cite this article

Kuhn, T., Zielesny, A. & Steinbeck, C. Creating chemo- and bioinformatics workflows, further developments within the CDK-Taverna Project. Chemistry Central Journal 3, P42 (2009). https://doi.org/10.1186/1752-153X-3-S1-P42

Download citation

Keywords

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

BMC Chemistry

ISSN: 2661-801X

Contact us