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» Predicting Nucleolar Proteins Using Support-Vector Machines
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BMCBI
2010
176views more  BMCBI 2010»
13 years 7 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...
BMCBI
2008
138views more  BMCBI 2008»
13 years 7 months ago
Application of nonnegative matrix factorization to improve profile-profile alignment features for fold recognition and remote ho
Background: Nonnegative matrix factorization (NMF) is a feature extraction method that has the property of intuitive part-based representation of the original features. This uniqu...
Inkyung Jung, Jaehyung Lee, Soo-Young Lee, Dongsup...
BMCBI
2010
113views more  BMCBI 2010»
13 years 7 months ago
Improving performance of mammalian microRNA target prediction
Background: MicroRNAs (miRNAs) are single-stranded non-coding RNAs known to regulate a wide range of cellular processes by silencing the gene expression at the protein and/or mRNA...
Hui Liu, Dong Yue, Yidong Chen, Shou-Jiang Gao, Yu...
IROS
2006
IEEE
247views Robotics» more  IROS 2006»
14 years 1 months ago
Towards Open-Ended 3D Rotation and Shift Invariant Object Detection for Robot Companions
- Robot companions need to be able to constantly acquire knowledge about new objects for instance in order to detect them in the environment. This ability is necessary since it is ...
Jens Kubacki, Winfried Baum
RECOMB
2007
Springer
14 years 7 months ago
Minimizing and Learning Energy Functions for Side-Chain Prediction
Abstract. Side-chain prediction is an important subproblem of the general protein folding problem. Despite much progress in side-chain prediction, performance is far from satisfact...
Chen Yanover, Ora Schueler-Furman, Yair Weiss