Combining data and text mining techniques for yeast gene regulation prediction: a case study

Authors:
Mark-A. Krogel;Marcus Denecke;Marco Landwehr;Tobias Scheffer
Affiliations:
University of Magdeburg, FIN/IWS, Universitätsplatz 2, Magdeburg, Germany;University of Magdeburg, FIN/IWS, Universitätsplatz 2, Magdeburg, Germany;Leibniz Institute for Neurobiology, Magdeburg, Germany;University of Magdeburg, FIN/IWS, Universitätsplatz 2, Magdeburg, Germany
Venue:
ACM SIGKDD Explorations Newsletter
Year:
2002

Citing 3
Cited 2

KDD Cup 2001 report

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Abstract

In order to solve task 2 of the KDD Cup 2002, we exploited various available information sources. In particular, use of relational information describing the interactions among genes and information automatically extracted from scientific abstracts improves the accuracy of our predictions.