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DIS
1999
Springer
13 years 9 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 6 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 5 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»
13 years 10 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 7 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