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BMCBI
2010
132views more  BMCBI 2010»
15 years 1 months ago
Data structures and compression algorithms for high-throughput sequencing technologies
Background: High-throughput sequencing (HTS) technologies play important roles in the life sciences by allowing the rapid parallel sequencing of very large numbers of relatively s...
Kenny Daily, Paul Rigor, Scott Christley, Xiaohui ...
112
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BMCBI
2008
123views more  BMCBI 2008»
15 years 1 months ago
Validation of protein models by a neural network approach
Background: The development and improvement of reliable computational methods designed to evaluate the quality of protein models is relevant in the context of protein structure re...
Paolo Mereghetti, Maria Luisa Ganadu, Elena Papale...
130
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JMLR
2006
140views more  JMLR 2006»
15 years 1 months ago
Active Learning in Approximately Linear Regression Based on Conditional Expectation of Generalization Error
The goal of active learning is to determine the locations of training input points so that the generalization error is minimized. We discuss the problem of active learning in line...
Masashi Sugiyama
BMCBI
2010
126views more  BMCBI 2010»
15 years 1 months ago
Antisense DNA parameters derived from next-nearest-neighbor analysis of experimental data
Background: The enumeration of tetrameric and other sequence motifs that are positively or negatively correlated with in vivo antisense DNA effects has been a useful addition to t...
Donald M. Gray, Carla W. Gray, Byong-Hoon Yoo, Tzu...
KDD
2007
ACM
148views Data Mining» more  KDD 2007»
16 years 2 months ago
Scalable look-ahead linear regression trees
Most decision tree algorithms base their splitting decisions on a piecewise constant model. Often these splitting algorithms are extrapolated to trees with non-constant models at ...
David S. Vogel, Ognian Asparouhov, Tobias Scheffer