Automatic discovery of cross-family sequence features associated with protein function

Markus Brameier^*¹^,2 , Josien Haan^*¹ , Andrea Krings ¹ and Robert M MacCallum¹^,3

¹Stockholm Bioinformatics Center, Stockholm University, 106 91 Stockholm, Sweden

²Bioinformatics Research Center, University of Aarhus, 8000 Aarhus C, Denmark

³Division of Cell and Molecular Biology, Imperial College London, London SW7 2AZ, UK

author email corresponding author email* Contributed equally

BMC Bioinformatics 2006, 7:16doi:10.1186/1471-2105-7-16


Published:	12 January 2006

Additional files

Additional File 1:

As in Figure 2 of the article, the predictors are clustered with a 8 × 8 Kohonen Self-Organising Map (SOM). In this figure, the evolved annotation word boolean expression (from the annotation_classifier subroutine) are shown in full for each of the 500 evolved function predictors. Each boolean expression is separated by a semicolon. The A-type predictors are shown with upper case to identify them.

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Additional File 2:

Here we show the full list of the 150 most common annotation words after manual filtering. The filtering is performed in order to remove stopwords and words that do not contain any information about protein function. The filtered words are shown with strikethrough text.

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Additional File 3:

Additional supplementary material (includes files 1 and 2); gzipped tar archive; after unpacking, please open the file brameier2005/index.html in your web browser.

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