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Abstract: The biological sciences are undergoing an explosion in the amount of available data. New data analysis methods are needed to deal with the data. We present work using KDD to analyse data from mutant phenotype growth experiments with the yeast S. cerevisiae to predict novel gene functions. The analysis of the data presented a number of challenges: multi-class labels, a large number of sparsely populated classes, the need to learn a set of accurate rules (not a complete classification), and a... (Update)
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BibTeX entry: (Update)
A. Clare and R.D. King. Knowledge discovery in multi-label phenotype data. In L. De Raedt and A. Siebes, editors, 5th European Conference on Principles of Data Mining and Knowledge Discovery (PKDD2001), volume 2168 of Lecture Notes in Arti cial Intelligence, pages 42-53. Springer-Verlag, 2001. http://citeseer.ist.psu.edu/clare01knowledge.html More
@article{ clare01knowledge,
author = "Amanda Clare and Ross D. King",
title = "Knowledge Discovery in Multi-label Phenotype Data",
journal = "Lecture Notes in Computer Science",
volume = "2168",
pages = "42+",
year = "2001",
url = "citeseer.ist.psu.edu/clare01knowledge.html" }
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