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» Hierarchical exploration of large multivariate data sets
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RECOMB
1998
Springer
15 years 2 months ago
The hierarchical organization of molecular structure computations
The task of computing molecular structure from combinations of experimental and theoretical constraints is expensive because of the large number of estimated parameters (the 3D co...
Cheng Che Chen, Jaswinder Pal Singh, Russ B. Altma...
KDD
1997
ACM
92views Data Mining» more  KDD 1997»
15 years 1 months ago
Increasing the Efficiency of Data Mining Algorithms with Breadth-First Marker Propagation
This paper describes how to increase the efficiency of inductive data mining algorithms by replacing the central matching operation with a marker propagation technique. Breadth-fi...
John M. Aronis, Foster J. Provost
KDD
1994
ACM
125views Data Mining» more  KDD 1994»
15 years 1 months ago
Knowledge Discovery in Large Image Databases: Dealing with Uncertainties in Ground Truth
This paper discusses the problem of knowledge discovery in image databases with particular focus on the issues which arise when absolute ground truth is not available. It is often...
Padhraic Smyth, Michael C. Burl, Usama M. Fayyad, ...
KDD
2000
ACM
142views Data Mining» more  KDD 2000»
15 years 1 months ago
Automating exploratory data analysis for efficient data mining
Having access to large data sets for the purpose of predictive data mining does not guarantee good models, even when the size of the training data is virtually unlimited. Instead,...
Jonathan D. Becher, Pavel Berkhin, Edmund Freeman
BMCBI
2010
109views more  BMCBI 2010»
14 years 10 months ago
Application of machine learning methods to histone methylation ChIP-Seq data reveals H4R3me2 globally represses gene expression
Background: In the last decade, biochemical studies have revealed that epigenetic modifications including histone modifications, histone variants and DNA methylation form a comple...
Xiaojiang Xu, Stephen Hoang, Marty W. Mayo, Stefan...