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BMCBI
2010
179views more  BMCBI 2010»
13 years 7 months ago
A semi-supervised learning approach to predict synthetic genetic interactions by combining functional and topological properties
Background: Genetic interaction profiles are highly informative and helpful for understanding the functional linkages between genes, and therefore have been extensively exploited ...
Zhuhong You, Zheng Yin, Kyungsook Han, De-Shuang H...
INFOCOM
2012
IEEE
11 years 10 months ago
Approximately optimal adaptive learning in opportunistic spectrum access
—In this paper we develop an adaptive learning algorithm which is approximately optimal for an opportunistic spectrum access (OSA) problem with polynomial complexity. In this OSA...
Cem Tekin, Mingyan Liu
STOC
1993
ACM
141views Algorithms» more  STOC 1993»
13 years 11 months ago
Bounds for the computational power and learning complexity of analog neural nets
Abstract. It is shown that high-order feedforward neural nets of constant depth with piecewisepolynomial activation functions and arbitrary real weights can be simulated for Boolea...
Wolfgang Maass
BMCBI
2006
123views more  BMCBI 2006»
13 years 7 months ago
SBEAMS-Microarray: database software supporting genomic expression analyses for systems biology
Background: The biological information in genomic expression data can be understood, and computationally extracted, in the context of systems of interacting molecules. The automat...
Bruz Marzolf, Eric W. Deutsch, Patrick Moss, David...
ICANN
2007
Springer
14 years 1 months ago
Identifying Binding Sites in Sequential Genomic Data
The identification of cis-regulatory binding sites in DNA is a difficult problem in computational biology. To obtain a full understanding of the complex machinery embodied in genet...
Mark Robinson, Cristina González Castellano...