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» TargetSpy: a supervised machine learning approach for microR...
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BMCBI
2010
176views more  BMCBI 2010»
13 years 5 months ago
TargetSpy: a supervised machine learning approach for microRNA target prediction
Background: Virtually all currently available microRNA target site prediction algorithms require the presence of a (conserved) seed match to the 5' end of the microRNA. Recen...
Martin Sturm, Michael Hackenberg, David Langenberg...
ALMOB
2008
127views more  ALMOB 2008»
13 years 5 months ago
HuMiTar: A sequence-based method for prediction of human microRNA targets
Background: MicroRNAs (miRs) are small noncoding RNAs that bind to complementary/partially complementary sites in the 3' untranslated regions of target genes to regulate prot...
Jishou Ruan, Hanzhe Chen, Lukasz A. Kurgan, Ke Che...
BMCBI
2008
141views more  BMCBI 2008»
13 years 5 months ago
MiRTif: a support vector machine-based microRNA target interaction filter
Background: MicroRNAs (miRNAs) are a set of small non-coding RNAs serving as important negative gene regulators. In animals, miRNAs turn down protein translation by binding to the...
Yuchen Yang, Yu-Ping Wang, Kuo-Bin Li
NAR
2006
142views more  NAR 2006»
13 years 4 months ago
miRNAMap: genomic maps of microRNA genes and their target genes in mammalian genomes
Recent work has demonstrated that microRNAs (miRNAs) are involved in critical biological processes by suppressing the translation of coding genes. This work develops an integrated...
Paul Wei-Che Hsu, Hsien-Da Huang, Sheng-Da Hsu, Li...
EPIA
2003
Springer
13 years 10 months ago
Adaptation to Drifting Concepts
Most of supervised learning algorithms assume the stability of the target concept over time. Nevertheless in many real-user modeling systems, where the data is collected over an ex...
Gladys Castillo, João Gama, Pedro Medas