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DIS
1999
Springer
13 years 11 months ago
The Melting Pot of Automated Discovery: Principles for a New Science
After two decades of research on automated discovery, many principles are shaping up as a foundation of discovery science. In this paper we view discovery science as automation of ...
Jan M. Zytkow
APBC
2006
181views Bioinformatics» more  APBC 2006»
13 years 8 months ago
Analyzing Inconsistency Toward Enhancing Integration of Biological Molecular Databases
: The rapid growth of biological databases not only provides biologists with abundant data but also presents a big challenge in relation to the analysis of data. Many data analysis...
Yi-Ping Phoebe Chen, Qingfeng Chen
BMCBI
2007
145views more  BMCBI 2007»
13 years 7 months ago
Improved benchmarks for computational motif discovery
Background: An important step in annotation of sequenced genomes is the identification of transcription factor binding sites. More than a hundred different computational methods h...
Geir Kjetil Sandve, Osman Abul, Vegard Walseng, Fi...
CSB
2005
IEEE
189views Bioinformatics» more  CSB 2005»
14 years 1 months ago
Learning Yeast Gene Functions from Heterogeneous Sources of Data Using Hybrid Weighted Bayesian Networks
We developed a machine learning system for determining gene functions from heterogeneous sources of data sets using a Weighted Naive Bayesian Network (WNB). The knowledge of gene ...
Xutao Deng, Huimin Geng, Hesham H. Ali
AAAI
2008
13 years 9 months ago
Zero-data Learning of New Tasks
We introduce the problem of zero-data learning, where a model must generalize to classes or tasks for which no training data are available and only a description of the classes or...
Hugo Larochelle, Dumitru Erhan, Yoshua Bengio